Research

My research interests fall broadly within health informatics, artificial intelligence (AI) in medicine, and health equity. My work is currently focused on four key areas:

  1. Health AI
    • predictive modeling using all forms of health data
    • examining the role of AI in health disparities
    • using AI to advance health equity
  2. Health Disparities
    • identifying and quantifying health disparities using EHR data
    • understanding causes of disparities
    • exploring measures to mitigate / eliminate disparities and advance health equity
  3. 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 reduce / mitigate AI bias and unfair outcomes
  4. 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 am 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.