Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS
Profile
Prof Hui JI
Principal Investigator
Hui Ji is a Professor at the Department of Mathematics in the National University of Singapore (NUS). He also serves as the Director of the Centre for Data Science and Machine Learning, NUS.
His long time research program can be roughly classified into the following sub-programs with close relationship.
1. Mathematical theory and tools for data sciences
2. Machine learning and its applications in robotics and medicine
3. Computational vision and image processing
Singapore - NUS
Principal Investigators
BloodCounts!
Research Interest
- Applied Mathematics
- Deep Learning
- Imaging Science and Deep Learning
Key Publications
Y. Quan, T. Zheng, and H. Ji,
“Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising,”
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Y. Quan, X. Qin, T. Pang, and H. Ji,
“Siamese Cooperative Learning for Unsupervised Image Reconstruction from Incomplete Measurements,”
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
X. Qin, Y. Quan, T. Pang, and H. Ji,
“Ground-Truth-Free Meta-Learning for Deep Compressive Sampling,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Wang, J. Li, and H. Ji,
“Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Pang, H. Zheng, Y. Quan, and H. Ji,
“Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising,”
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Achievements
2015– 2018: Dean’s Chair Associate Professorship, NUS
2010: Young Scientist Award, Faculty of Science, NUS