People

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

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.

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.

Katrina Hueniken

MSc student, Biostatistics, Dalla Lana School of Public Health

Katrina Hueniken holds a Bachelor in psychology and a Master of Public Health, and is pursuing a second Master's degree in Biostatistics at the University of Toronto. She is currently completing a practicum in Dr. Felsky's lab.

 

Katrina is also working as a statistician at the Princess Margaret Cancer Centre, focusing on clinical epidemiology research on cancer prognosis and patient quality of life. She is particularly interested in applying statistical learning methods to advance personalized medicine and improve patient care.

Micaela Consens

Undergraduate, Computer Science and Bioinformatics

Co-supervised with Dr. Shreejoy Tripathy

 

Micaela Consens is in her third year of a Bioinformatics Specialist and Computer Science Major at U of T. She works part time at Sick Kids Centre for Computational Medicine as a developer and is the Graphic Designer for Women In Computer Science (WiCS) at U of T.

Bianca Pokhrel

Undergraduate, Bioinformatics/Computational Biology and Statistics

Currently Bianca is a fourth year student at U of T doing a Bioinformatics Specialist and a Statistics Minor. She has worked at the OICR as a research student to analyse nanopore sequencing reads to both simulate and identify gene fusions as drivers of cancers. She is passionate about the applications of computer science in the field of personalized medicine.

Wing Chung Jessie Lam

Undergraduate, Computer Science and Bioinformatics

Co-supervised with Dr. Shreejoy Tripathy

 

Jessie Lam is a third-year undergraduate student at the University of Toronto majoring in Computer Science and Bioinformatics. She is currently the Conference Chair for Scientista at UofT.

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