Biography
I am a co-founding partner of Interpretable AI which delivers interpretable methods and solutions for machine learning and artificial intelligence. I obtained my Ph.D. in Operations Research at the Massachusetts Institute of Technology, supervised by Prof. Dimitris Bertsimas. My primary research interests are at the intersection between machine learning and optimization, with applications to personalized medicine.
My research in machine learning involves developing missing data imputation methods using optimization and machine learning, as well as statistical learning algorithms that are robust to uncertainties in data. My research in health care focuses on personalizing diabetes management using electronic medical records, and advancing cancer patient care with improved predictive and prescriptive modeling.
Prior to MIT, I worked in Health Economics and Outcomes Research at Analysis Group, Boston for two years, and researched at Warwick Business School, UK in data science.
My abbreviated résumé can be found here.