Profile

Dr Elias EBRAHIMZADEH

Research Fellow

Dr Elias Ebrahimzadeh obtained his mathematics and physics diploma under the supervision of NODET (National Organization for Developing Exceptional Talent) in 2003. He completed his Ph.D. studies in Biomedical Engineering in 2019 where his primary focus was on the localisation of the epileptic foci using simultaneous EEG-fMRI recording in patients with epilepsy. Specifically, he developed a novel approach based on the ICA theory for this purpose. To enhance his research, he joined the research team at the University of Calgary as a Visiting PhD Researcher.

Dr Ebrahimzadeh received a fully funded postdoctoral position at Oakland University in the field of NMR. He worked in the Neuroimaging Laboratory, at the School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran as a Postdoctoral Research Fellow applying multimodal techniques in the fields of Neuroscience and Neurophysics. He has authored/coauthored more than 40 publications in international journals.

Dr Elias Ebrahimzadeh joined CLIC as a Research Fellow in CLIC’s Neuroimaging Workgroup and was the main personnel in charge of CLIC’s MRI protocol.

Past Members

Past Members

Research Interest

Dr Elias Ebrahimzadeh's interest in research and education involves neurosciences, biomedical signal processing, artificial neural network, statistical pattern recognition, system identification, bioelectromagnetic, machine learning, and image processing. He is fond of the interplay of these areas towards the study of the brain.

- Cognitive Neuroscience
- Simultaneous EEG-fMRI Analysis
- Biomedical Signal Processing
- Artificial Neural Network
- Statistical Pattern Recognition
- Image Processing
- Machine Learning
- System Identification

Key Publications

Google Scholar Link

Sadjadi SM, Ebrahimzadeh E, Shams M, Seraji M and Soltanian-Zadeh H (2021) Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data. Front. Neurol. 12:645594. doi: 10.3389/fneur.2021.645594

Ebrahimzadeh, E., Manuchehri, M.S., Amoozegar, S. et al. A time local subset feature selection for prediction of sudden cardiac death from ECG signal. Med Biol Eng Comput 56, 1253–1270 (2018). https://doi.org/10.1007/s11517-017-1764-1

Ebrahimzadeh, E., Kalantari, M., Joulani, M., Shahraki. R.S., Fayaz, F., Ahmadie, F. Prediction of paroxysmal Atrial Fibrillation: A machine learning based approach using combined feature vector and mixture of expert classification on HRV signal. Comput Methods Programs Biomed 165, 53-67 (2018). https://doi.org/10.1016/j.cmpb.2018.07.014

Ebrahimzadeh E, Pooyan M, Bijar A (2014) A Novel Approach to Predict Sudden Cardiac Death (SCD) Using Nonlinear and Time-Frequency Analyses from HRV Signals. PLoS ONE 9(2): e81896. https://doi.org/10.1371/journal.pone.0081896

Ebrahimzadeh, E. and Pooyan, M. (2011) Early detection of sudden cardiac death by using classical linear techniques and time-frequency methods on electrocardiogram signals. Journal of Biomedical Science and Engineering, 4, 699-706. doi: 10.4236/jbise.2011.411087.

Achievements

He Ranked 1st Admitted Ph.D. of Biomedical Engineering at the University of Tehran, 2014 and consequently, obtained Ranked 2nd among more than 1,000 Electrical Engineering students in the nationwide university entrance exam for a Ph.D. degree.