Research

My research interests fall broadly within health informatics, artificial intelligence in medicine, and health equity. My work is primarily focused on two key areas:

  1. Bias in 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
    • examining the role of AI on health disparities
    • using AI to advance health equity
  2. 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.