I am a Ph.D. student in Information Systems at the Michael G. Foster School of Business, University of Washington. I’m fortunate to work under the supervision of Professor Yong Tan.
My research commences with the modeling of participant behavior encompassing search, learning, and decision-making processes, alongside examining market-level equilibrium in (digital) two-sided markets and communities. Leveraging the gleaned insights, the overarching aim is to augment AI systems, refine market designs, and inform policy regulations to maximize welfare quantity and ensure its equitable distribution among stakeholders, with a particular focus on pivotal sectors such as health, labor, education, creativity/innovation, and finance. Methodologically, I leverage econometric/statistical analyses (including structural/Bayesian models), analytical models, field/lab experiments, and machine learning/deep learning (especially reinforcement learning) 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. I was also fortunate to have the chance to participate in the weekly seminar led by Professor Guoqing Chen, Professor Xunhua Guo, and Professor Qiang Wei.
“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