Research
My research interests fall broadly within health informatics, artificial intelligence (AI) in medicine, and health equity. My work is primarily focused on two key areas:
- Health AI
- Predictive modeling using all forms of health data
- examining the role of AI in health disparities
- using AI to advance health equity
- AI Bias (with a specific focus on health AI)
- developing frameworks and approaches to define, detect, and quantify AI bias
- exploring and creating innovative approaches to mitigate AI bias and unfair outcomes
- Large Language Models (LLMs) in healthcare
- exploring novel healthcare applications
- evaluating clinical effectiveness and safety
- understanding the implications of LLMs in clinical settings
While I’m passionate about advancing technological frontiers with novel methods and approaches, my work is grounded in pragmatism. I believe that meaningful research must bridge the gap between innovative methodologies and tangible improvements in health outcomes. My ultimate hope is that my work will advance science in a way that makes a real difference in people’s lives, improves health outcomes, and reduces health disparities.