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.

Research

Selected Publications

Other professional activities

Work Experience

Interpretable AI (Co-Founding Partner, June 2018 to Current)

  • Develop and maintain Interpretable AI’s proprietary machine learning algorithms that deliver interpretability and state-of-the-art performance simultaneously
  • Lead the development of end-to-end business solutions using Interpretable AI’s technology

Analysis Group, Inc. (Analyst, July 2012 to May 2014)

  • Conducted Bayesian network meta-analyses synthesizing the evidence from published clinical trials to compare efficacy and safety across a network of treatment options.
  • Built cost-effectiveness Monte Carlo simulation models or Markov chain models in disease areas such as HIV, deep vein thrombosis, and multiple myeloma.
  • Developed and instructed the programming language R training course for 200+ employees across two offices, enabling managers and associates to conduct more efficient data analysis and build more advanced models.

Teaching Experience

  • Teaching assistant for Ph.D.-level course Machine Learning, Spring 2018
  • Instructor on data analytic software (R, Julia, and Python) for the Masters of Business Analytics program at Sloan School of Management, Massachusetts Institute of Technology, 2017.
  • Course manager for the Analytics Edge on EdX course offered to more than 20,000 registered students, Summer 2017.
  • Teaching assistant for the Analytics Edge at Sloan School of Management, Massachusetts Institute of Technology, Spring 2017 (Executive MBA), Spring 2016 (MBA).
  • Teaching assistant for courses in Computer Science, Mathematics, and Economics at Middlebury College, September 2009 to May 2012.

Talks

Review Activities