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Faculty Member

Farbod Abolhassani

Email Address(es)
Epidemiology Division
Adjunct Professor
SGS Status
Associate Member
Currently Accepting Doctoral Students?

Research Interests

  • Development of computer vision algorithms applied to diagnostic imaging (XR, CT, MR, US)
  • Development and validation of imaging biomarkers for population health
  • Deployment, evaluation and monitoring of health care AI models
  • Applications of deep learning in disease diagnosis, prognosis and treatment selection

Farbod Abolhassani is an entrepreneur, data scientist, and software engineer. He is passionate about building and implementing AI enabled technology solutions in the health sector.

Mr. Abolhasani is an Adjunct Professor at the Dalla Lana School of Public Health at the University of Toronto where his teaching focuses on the application of data science in health care. He is an Affiliate Scientist with Trillium Health Partner’s Institute for Better Health at the AI Deployment and Evaluation (AIDE) lab where he is focused on helping researchers and companies develop and validate safe and equitable healthcare AI models.

Previously, Mr. Abolhassani led the development of the analytics and data science consulting portfolio of Medtronic Canada, a fortune 500 medical device company. In his role as the Lead Data Science Consultant, Farbod led the team in the design and implementation of health care data science solutions in eight different hospitals across four different provinces. Further, Farbod led the team responsible for the development, design, and implementation of a proprietary artificial intelligence-powered anesthesia monitor which predicted cardiac surgery complications using physiological monitoring data which is currently in use in the operating rooms and intensive care units of one of Canada’s largest cardiac centers.

Mr. Abolhassani received his graduate training in Health Informatics from the Institute of Health Policy, Management and Evaluation (IHPME) at the University of Toronto where his training focused on leading health system transformations through a combination of expertise in health systems management with applied knowledge in information and communication technologies.