At GenAI Health Lab, we are driven by curiosity, creativity, and the belief that generative AI can transform the future of health. Our team of dedicated students and researchers works at the intersection of technology and healthcare, exploring bold new ideas and building innovative solutions.
From AI-driven drug discovery and synthetic data generation to health service chatbots and generative qualitative coding, our projects push the boundaries of what’s possible. In our fast-paced and collaborative environment, we embrace experimentation, learn from challenges, and stay committed to advancing knowledge that can make a real impact.
Get to know the researchers in our lab: see team profiles.
Research interests
- Artificial intelligence (AI) for public and population health
- AI in drug discovery
- AI for learning health systems
- Generative AI (GenAI) and synthetic data
- Evaluation of GenAI in health
- Health data quality and analytics
- Real world evidence
See selected publications for more information on our work.
Interested in working with us?
As part of who we are, we are always looking for new opportunities and innovations.
For students
Interested in becoming a student of the GenAI Health lab? We are looking for passionate students and researchers interested in exploring up-and-coming technology and ideas!
Please check out our page outlining how students can get involved.
For partners and collaborators
We partner with companies and research teams to co-create innovative solutions at the intersection of health and generative AI.
Connect with us if you’re looking to collaborate on cutting-edge projects.
News
Full Sailing into Artificial Intelligence!
A long-time member of the GenAI for Health research lab will be featured in a keynote session at the 2026 APHEO-OPHEN Conference as part of the “Full Sailing into Artificial Intelligence!” series. His presentation will explore the use of artificial intelligence to assess the quality of AI scribe tools in infectious disease case management, highlighting the importance of evaluating emerging technologies in real-world public health settings. This work reflects the lab’s commitment to advancing innovative, data-driven approaches and showcases the impact of its members in shaping the future of AI in health systems.
AI bridging the gap between health-care visits
Modern health care often leaves patients unsupported between visits, contributing to worsening conditions and preventable readmissions. Doro, a startup from the University of Waterloo’s Velocity program co-founded by Rastin Rassoli, is developing clinically guided AI tools to bridge these gaps by continuously supporting patients before, between, and after care. Using patient-reported data, the platform monitors symptoms, offers evidence-based mental health support, and helps clinicians maintain better visibility into patient well-being. Designed specifically for clinical use, Doro emphasizes safety, privacy, and validation, and is being tested in areas such as mental health, addiction, and chronic illness, with the goal of improving recovery and reducing strain on the health-care system.
Using AI to accelerate drug development
A University of Waterloo research team is using machine learning to speed up drug development by analyzing complex pharmaceutical data and predicting drug properties, interactions, and safety outcomes. Led by Dr. Helen Chen, with PhD candidate Bing Hu and applied mathematician Dr. Anita Layton, the team integrates biological and medical knowledge into their models to improve accuracy and better reflect real-world drug behavior.