"Knowledge is Speaking, Wisdom is Listening" - Jimi Hendrix

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Daniel Felsky, PhD

Principal Investigator

Dr. Daniel Felsky is an Independent Scientist and Head of Whole Person Modelling in the Krembil Centre for Neuroinformatics at CAMH and Assistant Professor in the Department of Psychiatry and Institute of Medical Science (IMS) at the University of Toronto.

Dr. Felsky completed his PhD in neuroimaging and genetics of Alzheimer’s disease at IMS in 2015. Following this, Dr. Felsky completed postdoctoral fellowships at the Anne Romney Center for Neurologic Diseases at Brigham and Women’s Hospital, Harvard Medical School, in Boston, and the Centre for Translational and Computational Neuroimmunology at Columbia University Medical Centre in New York.

Dr. Felsky has experience across several areas including structural brain imaging, human genomics and transcriptomics, neuroimmunology, biostatistics, psychiatric epidemiology, and study design. In addition to his research, Dr. Felsky is a passionate teacher, and has taught globally as a Fellow for the Harvard Global Initiative for Neuropsychiatric Genetics Education in Research, co-sponsored by the Stanley Centre for Psychiatric Research at the Broad Institute of MIT and Harvard.


Milos Milic

Research Analyst

Milos Milic is a Research Analyst working primarily with Dr. Felsky in developing standardised internal protocols for data curation.


Milos completed his first Masters in the department of Cell and Systems Biology at the University of Toronto under Dr. Ulrich Tepass where he focused on successfully characterising the function of Drosophila gene CG34347 via confocal microscopy and genetic recombination. He has recently completed a Masters of Data Science at the University of British Columbia where he helped develop a machine learning model that can identify iron ore veins from images.


He is passionate about machine learning, especially leveraging labelled image data in their application to healthcare diagnostics.


Peter Zhukovsky, PhD

Postdoctoral Fellow

Primarily supervised by Dr. Aristotle Voineskos

Dr. Peter Zhukovsky (PhD, Experimental Psychology and Psychiatry, University of Cambridge, UK) is a postdoctoral fellow. Peter’s work focuses on the neurobiological mechanisms of major depressive disorder, particularly on late-life treatment resistant depression. In particular, he uses whole brain structural and functional connectivity to identify depression “biotypes” in large scale databases (UK Biobank) and predict cognitive outcomes in a depression treatment trial (OPTIMUM dataset). He combines functional connectivity measures from resting-state fMRI and structural connectivity measures from morphometric similarity mapping and diffusion weighted images with advanced statistical approaches such as partial least squares, clustering and deep neural networks. He hopes to reveal the associations between brain connectivity, cognition and clinical symptoms.


Mohamed Abdelhack, PhD

Postdoctoral Fellow

Mohamed is a Postdoctoral Fellow working on using machine and deep learning to model psychiatric disorders.

He previously worked as a Postdoctoral Researcher in Washington University in St. Louis where he was building machine learning models to predict post-surgical medical complications. He also worked as a researcher in Kyoto University Hospital studying neural activity markers of Schizophrenia using brain decoding techniques. His doctoral work in Kyoto University focused on using deep learning models to understand robustness of human brain in recognizing degraded visual input.


He possesses a wide range of skills in computational neuroscience, neural imaging, machine and deep learning, and electronic design.


Stuart Matan-Lithwick, PhD

Postdoctoral Fellow

Co-supervised with Dr. Shreejoy Tripathy

Stuart is a postdoctoral candidate in the Felsky and Tripathy labs, who is using polygenic scoring and mixed modelling to study the specific genes and environments that contribute to the appearance of co-morbid conditions in Alzheimer's disease patients.


Stuart is also an academically trained high school educator, and a vocal advocate on behalf of the vision loss community, himself being visually impaired. Outside of academic circles, Stuart is an amateur singer and vocal percussionist with the A Cappella choir SoundCrowd, and a long distance runner. Stuart is also a dad to Grace, and is loving every minute.


Jonáš Rybníček

PhD student, Department of Physiology

Co-supervised with Dr. Evelyn Lambe

Jonas is a graduate student at the University of Toronto, and a member of the Collaborative Program in Neuroscience. He is working toward his PhD in the laboratory of Dr. Evelyn Lambe and is working with Dr. Felsky on a project focusing on cholinergic signaling in Alzheimer’s disease.

Following the completion of his bachelor studies in Biomedical science at the University of Dundee, Jonas went to Boston as a visiting student in a systems biology laboratory at the Massachusetts Institute of Technology and since then has also completed a research assistantship focused on multiple sclerosis, at the University of Munich.

Jonas is passionate about research in neurological disorders and wants to implement a multi-disciplinary approach in his thesis work, combining bioinformatics, electrophysiology, and behavioral techniques.


Amin Kharaghani

MSc student, Biostatistics, Dalla Lana School of Public Health

Amin Kharaghani is a graduate student at University of Toronto, studying Biostatistics with an emphasis on machine learning at Dalla Lana School of Public Health. As part of his graduate studies, he is working with Dr. Felsky as a practicum student, focusing on Alzheimer Disease.

Amin completed his undergraduate studies at University of Toronto Mississauga majoring in Mathematics and Statistical Sciences. Amin is passionate about education; he works at University of Toronto as a teaching assistant at Mathematical and Computational Sciences department.


Amin is interested in machine learning and deep learning and their applications in genetics and, behavioural sciences.


Earvin Tio

MSc Student, Institute of Medical Science

Earvin Tio is a graduate student with the Institute of Medical Science and a member of the Collaborative Program in Neuroscience. His research focuses on uncovering neuroimmune mechanisms that underlie suicidal ideation by leveraging large cohort studies and machine learning.

Earvin graduated from the University of Waterloo with a Bachelor of Applied Science in Systems Design Engineering and a specialization in Artificial Intelligence. During his undergraduate studies, Earvin also had the opportunity to study abroad in Switzerland at the École polytechnique fédérale de Lausanne, studying computer science.


Earvin is passionate about destigmatizing mental illness. He actively works with GradMinds, the University of Toronto's graduate student mental health committee, and regularly contributes to Elemental Magazine, the University of Toronto's official mental health magazine.


Mu Yang

MSc Student, Biostatistics, Dalla Lana School of Public Health

Mu is a graduate master student at Dalla Lana School of Public Health, University of Toronto. He is joining Dr. Felsky's lab as a practicum student, focusing on computational modelling of cognitive trajectories in aging.

Mu completed his undergraduate studies at University of Waterloo majored in Mathematics with minors of Statistics and Psychology. After graduation, Mu spent a year and a half in the Chinese internet industry to improve his professional skills such as data manipulation and computer simulation.

Mu is passionate about integrating his knowledge of data science with fields of psychology and genetic studies.

Past Members

Alyssa Cannitelli


Micaela Consens


Roberta Dolling-Boreham


Katrina Hueniken


Wing Chung Jessie Lam


Sejal Patel, PhD


Bianca Pokhrel


Emily Wiljer