An Artificial Intelligence-Driven Platform for the Surveillance of Substance Use Risks in Canada: Development, Validation, and Policy Implications
Dr. Vijay Mago
Associate Professor and Chair of the School of Health Policy and Management, York University
Date: Friday, February 7, 2025
Time: 1–2 p.m. EST
Host: Dr. Venkat Bhat
Location: In-person and virtual
Li Ka Shing Knowledge Institute, Room 240, and via Zoom
Refreshments will be served.
Lecture Takeaways
The main takeaways are as follows:
- Understand the key design considerations and best practices for developing robust public health surveillance systems.
- Compare the use of traditional Natural Language Processing (NLP) algorithms versus Large Language Model (LLM)-based approaches for data extraction, analysis, and interpretation
- Recognize the challenges, practical considerations, and opportunities involved in implementing AI-driven solutions for public health monitoring.
Biography
Dr. Vijay Mago is an Associate Professor and Chair of the School of Health Policy and Management at York University, where he conducts cutting-edge research in health informatics, machine learning, and natural language processing. Throughout his career, he has fostered extensive collaborations with academic institutions across Canada and internationally, including partnerships in India, the United States, Greece, Europe, and the United Kingdom. These collaborations extend beyond academia, encompassing industry, government, and nonprofit organizations, underscoring the interdisciplinary and applied nature of his work.
Dr. Mago has secured over $3.5 million in external research funding from diverse sources, including Canada’s tri-council agencies (NSERC and SSHRC), as well as government bodies, public sector organizations, and nonprofits. He regularly publishes his research in high-impact international journals and tier-1 conferences, showcasing the breadth and depth of his scholarship.
A dedicated mentor, Dr. Mago has an extensive record of supervising graduate students whose projects advance the fields of informatics and machine learning. Additionally, he serves as an Associate Editor for several reputable journals and contributes to the academic community as a program committee member for numerous international conferences.
No sign-up is required. For more information, contact the iBEST coordinator at ibest@torontomu.ca.
