My primary areas of interests include Algorithmic Game Theory, Optimization, and Machine Learning---in particular, multi-agent learning, incentive mechanisms, market algorithms, scheduling etc. Thus far, I have worked on problems arising from real-world scenarios like online crowd-sourcing, resource allocation, healthcare, dynamic pricing in transportation, ride sharing etc. I intend to find newer avenues where I can apply game theoretic, optimization and machine learning techniques to tackle practical and pressing problems which we face today.

Prior to Harvard, I was a Visiting Researcher at Google Research, where I worked on preventive healthcare intervention planning, in collaboration with a non-profit called ARMMAN to help provide timely preventive-care information to pregnant families, targeted towards low-income communities. Before joining Google, I pursued Ph.D. at the Department of Computer Science and Automation (CSA), Indian Institute of Science (IISc) on fair decision making in resource allocation, recommendation, and prediction problems. During my Ph.D., I was a recipient of Google Ph.D. Fellowship award. My dissertation received the Best thesis recognitions from INAE (Indian National Academy of Engineering) and from IISc.