Bio

I work on developing new machine learning and optimization methods in applications that typically interface with people, such as retail and next-generation transportation. My current and prior work experiences include working with/at the University of Illinois at Chicago, Xerox Research, Massachusetts Institute of Technology, Citadel Investments, Apple, State Street Global Advisors, and Texas Instruments to name a few.

You can visit DBLP, Arxiv, SSRN or Google Scholar to see some of the research threads I have pursued (some presentations are also available on youtube).

Some examples research outcomes are:

• Enhancing supervised learning in the presence of operational information
• Solving transportation problems such as scheduling, crowdshipping and enabling fair ride-shares
• Optimizing and personalizing recommendations and prices assuming realistic user behavior models
• Product pricing and learning in economic and competitive settings (e.g., capturing loyalty)
• Designing theoretically well-behaved online and reinforcement learning methods for applications involving personalization by exploiting the underlying application specific structure.