I am a second-year Ph.D. student at the Michael G. Foster School of Business, University of Washington. I’m fortunate to work under the supervision of Professor Yong Tan.
My current research focuses on the design and evaluation of IT-enabled interventions, which can be further divided into two lines: On one hand, I am interested in how AI systems/market design/peers’ behavior affect users’ decision-making process and thereby influence economic value/social welfare. On the other hand, I am also interested in designing models/algorithms to understand dynamic processes and optimize policies on online platforms. My research topics are quite broad, including Artificial Intelligence, Fintech (Blockchain), Cloud Computing, Social Media, Online Matching, Online Healthcare, Online Education, Video Games, Live Streaming/Short Video, Digital Marketing, etc. Methodologically, I leverage econometric/statistical models (including structural models), analytical models, field/lab experiments, and machine learning/deep learning (including reinforcement learning framework) to conduct design, analyze data, infer causality, and optimize policies.
I also enjoy cooperating with all kinds of enterprises to tackle real-world problems. People (e.g., managers, designers, and engineers) in the industry always inspire me.
Before my Ph.D. career, I studied Information Management and Information Systems at the School of Economics and Management, Tsinghua University. I was glad to cultivate research skills under the guidance of Professor Kevin Hong and Professor Bo Li during that period.
“Models tend to be useful when they are simultaneously simple enough to fit a variety of behaviors and complex enough to fit behaviors that need the help of an explanatory model.” —— Thomas C. Schelling
“Each of these ubiquitous marketplaces has found a way to succeed not only in making markets thick, uncongested, and safe, but also in making them simple to use.” —— Alvin E. Roth