Mina Mirjalili
Postdoctoral Researcher @CAMH
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WORK HISTORY
Postdoctoral Researcher @CAMH
Toronto, ON, CA
The primary goal of my postdoctoral research is to personalize non-invasive brain stimulation by integrating electric field (E-field) modeling with AI-driven analysis to improve cognitive outcomes in clinical populations, specifically individuals with depression and mild cognitive impairment (MCI).• I lead a clinical trial that personalizes transcranial alternating current stimulation (tACS) in MCI patients using individualized head models to optimize E-field delivery and maximize stimulation efficacy. This work bridges computational modeling with real-world clinical application.• Using electric field simulations and neuroimaging data, I identify brain regions and stimulation parameters most associated with cognitive improvement. These insights are used to tailor stimulation protocols to each patient’s unique brain anatomy.• I also develop machine learning models to predict clinical response to brain stimulation based on neurophysiological and anatomical features. This includes supervised learning pipelines, feature importance analysis, and cross-validation to ensure robust prediction performance.
EDUCATION
University of Tehran
Bachelor of Science - BS, Electrical Engineering
University of Toronto
Doctor of Philosophy - PhD, Neuroscience
University of Tehran
Master of Science - MS, Biomedical Engineering
ABOUT MINA MIRJALILI
As an electrical engineer with a biomedical engineering background, my research interests now center around leveraging machine learning (ML) and computational models to address real-world clinical and commercial challenges.During my postdoctoral research, I focus on personalizing brain stimulation using individualized electric field modeling and ML-based analytics to enhance therapeutic efficacy—particularly in neuropsychiatric populations. My work aims to bridge the gap between engineering innovations and practical healthcare applications, driving precision medicine forward through data-driven neuroscience.During my Ph.D, I successfully combined ML methods and causal discovery algorithms with EEG data to explore novel brain stimulation interventions for preventing neurological disorders like Alzheimer\'s disease.In my industry experience as a machine learning engineer, I actively contributed to various projects involving NLP methods, particularly in sentiment analysis and speech recognition.Google Scholar: https://scholar.google.com/citations?hl=en & & view_op=list_works & sortby=pubdate
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