I am an incoming Assistant Professor in the Department of Computer Science at Rutgers University (starting in January 2024). My research interests lie in the intersection of artificial intelligence and economics. My recent work focuses on studying multi-agent, game-theoretic environments where agents interact, often with the aid of algorithms, and agents' desires may not easily and reliably match up. Examples include online platforms, financial markets, a rush-hour commute, and a game of poker.
Through integrating computational tools (e.g., machine learning, simulation techniques) and economic principles (e.g., game theory), I explore two broad categories of problems:
(i) understanding agent incentives and behavior to design rules or systems that can lead to socially optimal outcomes from agent interactions;
(ii) addressing computational challenges that arise when operating or analyzing multi-agent systems.
My work finds applications to economic platforms, recommender systems, financial markets (centralized and decentralized), blockchain and its applications, social networks, etc.
Before Rutgers, I was a postdoctoral fellow in Computer Science and EconCS group at Harvard University, working with David C. Parkes. In 2021, I completed my Ph.D. in Computer Science at the University of Michigan, advised by Michael P. Wellman. I have worked as Ph.D. research intern at Microsoft Research and J.P. Morgan AI Research.
My group at Rutgers is recruiting for 24' (application link)! If you're interested in joining or working with our group, please take a look at this page.