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
Integrating AI Scribe Technology into Public Health Workflows
Nauman Shakeel presented his paper Integrating AI Scribe Technology into Public Health Workflows: Simulation and Field Evaluation in Disease Case Management at the Medical Informatics Europe (MIE) 2026 conference May 28, 2026.
This project explored the integration of AI-assisted documentation into infectious disease management workflows within public health settings, with the goal of reducing administrative burden and improving workflow efficiency.
Celebrating a Successful Thesis Defense
We are pleased to announce yet another successful thesis defence this week, this time to Yixin Li on successfully defending his thesis, "A Comprehensive Evaluation Framework for Synthetic ECG: Assessing Fidelity, Utility, and Privacy", April 30, 2026.
Congratulations, Yixin, on this well-deserved accomplishment!
Celebrating a Successful Thesis Defense
We are pleased to congratulate one of our lab members Kateryna Padalko on the successful defence of her thesis, "Adaptive Differential Privacy Budgeting Strategy for Optimizing Synthetic Data Generation and Privacy Protection in Healthcare".
Congratulations Kateryna on this well-deserved accomplishment!