"Knowledge is Speaking, Wisdom is Listening" - Jimi Hendrix
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.
Daniel Felsky PhD
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.
MSc student, Biostatistics, Dalla Lana School of Public Health
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.
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.
Undergraduate, Computer Science and Bioinformatics