Faculty Affiliates

Venkat Bhat, MD MSc FRCPC DABPN is a psychiatrist, clinician-scientist, and Associate Professor of Psychiatry at the University of Toronto with cross-appointments at Unity Health and University Health Network. He leads the AI for Mental Health (AI-M) Program and serves as Mental Health Community of Practice Lead at T-CAIREM, advancing AI for mental health and at the interface of mental health and medical illness. He directs federally funded, interdisciplinary initiatives that bring stakeholders across Canada together in areas including wellness and resilience in the Canadian Armed Forces, depression, and PTSD, emphasizing the bidirectional relationship between AI and neuroscience and the safe, equitable, and scalable integration of AI into clinical care, education, and research.

Nihal Haque MD FRCPC is a physician specializing in geriatric medicine at North York General Hospital in Toronto, Canada, and an Adjunct Assistant Professor at the University of Toronto. He has obtained certification in Artificial Intelligence (AI) in Healthcare from the Michener Institute and Harvard T.H. Chan School of Public Health. He is a physician representative of his hospital’s AI working group and is part of an interdisciplinary team that recently obtained federal funding through Canada Health Infoway to develop AI solutions to reduce healthcare worker burnout. With a focus on improving patient outcomes through innovations in healthcare, Dr. Haque leads AI-driven research in other areas as well, such as improving delirium care and enhancing medical education in Geriatric Medicine. He is also actively involved with the TCAIREM education committee as a faculty advisor on AI in medical education.

Alex Mariakakis is an Assistant Professor in the University of Toronto's Department of Computer Science and an Affiliate Scientist at KITE@UHN. He runs the Computational Health and Interaction (CHAI) Lab, which leverages ubiquitous technologies like smartphones and wearables to develop innovative mobile health applications. Many of these applications rely on digital signal processing and machine learning to analyze and visualize sensor data, but his group's research also spans other areas, including novel sensing techniques and human-computer interaction.