Program Director
Alireza Sadeghian PhD
Professor, Department of Computer Science, Faculty of Science, Toronto Metropolitan University;
Chair, IEEE Signals & Computational Intelligence Chapter, Toronto Section
Affiliate Scientist, Li Ka Shing Knowledge Institute, Keenan Research Centre, St. Michael’s Hospital
Founding Director, Advanced Artificial Intelligence Lab (AI2)
Alireza Sadeghian, PhD is Professor in the Department of Computer Science at Toronto Metropolitan University, where he teaches undergraduate and graduate courses in Deep Learning, Soft Computing, and Machine Intelligence. He currently serves as Program Director for the Applied AI in Medicine Certificate Program at the Temerty Faculty of Medicine, University of Toronto. He is also an Affiliate Scientist at the Li Ka Shing Knowledge Institute and Keenan Research Centre for Biomedical Science at St. Michael’s Hospital, where he previously led AI/ML analytics research in healthcare as part of the Institute for Biomedical Engineering, Science, and Technology (iBEST).
His contributions to education and research have been recognized with numerous awards, including the Dean’s SRC Research Award, IEEE Toronto’s Outstanding Leadership Award, and the YSGS Outstanding Contribution to Graduate Education Award. He has also been named among the Top 25 Canadian Scientists by the Royal Canadian Institute for the Advancement of Science. Dr. Sadeghian is actively involved in standards development for explainable AI through the IEEE, and serves on editorial boards for leading journals including Information Sciences, Applied Soft Computing, and Expert Systems.
In 2020, as part of a team led by Dr. Jane Batt, Alireza Sadeghian won the People’s Choice Award at St. Michael’s Hospital’s Angels Den competition for their presentation, Smart Garments: AI Therapy for Your Muscles.
Scientific Planning Committee
Michael Cusimano MD, FRCSC, DABNS, FACS, PhD, MHPE
Professor, Neurosurgery, Department of Surgery, Temerty Faculty of Medicine, University of Toronto
Shahin Hatami MD
Family Physician
Alexander Landry BSc
Resident, Department of Surgery, Temerty Faculty of Medicine, University of Toronto
Alireza Sadeghian PhD
Professor, Department of Computer Science, Faculty of Science, Toronto Metropolitan University;
Chair, IEEE Signals & Computational Intelligence Chapter, Toronto Section
Affiliate Scientist, Li Ka Shing Knowledge Institute, Keenan Research Centre, St. Michael’s Hospital
Founding Director, Advanced Artificial Intelligence Lab (AI2)
Suzan Schneeweiss MD, MEd, FRCPC
Professor of Paediatrics
Associate Dean, Continuing Professional Development, Temerty Faculty of Medicine, University of Toronto
Director of Education and Staff Emergency Paediatrician, Division of Paediatric Emergency Medicine, The Hospital for Sick Children
Devin Singh MBBS, MSc (Computer Science)
Staff Physician, Lead Clinical AI and Machine Learning in PEM at The Hospital for Sick Children;
Co-Founder & CEO Hero AI
David Wiljer PhD
Academic Director, Continuing Professional Development, Temerty Faculty of Medicine, University of Toronto;
Scientist, The Wilson Centre;
Executive Director, Education Technology and Innovation, University Health Network;
Professor, Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, and Department of Psychiatry, University of Toronto
Faculty Disclosure
It is the policy of University of Toronto, Faculty of Medicine, Continuing Professional Development to ensure balance, independence, objectivity, and scientific rigor in all its individually accredited or jointly accredited educational programs. Speakers and/or planning committee members, participating in University of Toronto accredited programs, are expected to disclose to the program audience any real or apparent conflict(s) of interest that may have a direct bearing on the subject matter of the continuing education program. This pertains to relationships within the last five (5) years with pharmaceutical companies, biomedical device manufacturers, or other corporations whose products or services are related to the subject matter of the presentation topic. The intent of this policy is not to prevent a speaker with a potential conflict of interest from making a presentation. It is merely intended that any potential conflict should be identified openly so that the listeners may form their own judgments about the presentation with the full disclosure of facts. It remains for the audience to determine whether the speaker’s outside interests may reflect a possible bias in either the exposition or the conclusions presented.