About

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. Before my Ph.D. career, I studied Information Management and Information Systems at the School of Economics and Management, Tsinghua University.

In general, I study how humans and AI behave and interact on online platforms to power smarter AI and platform designs. I employ a multidisciplinary approach that combines econometric methods (including structural estimation), field/laboratory experiments, analytical models, and machine learning algorithms (including reinforcement learning and large language models) to analyze data, infer causality, and optimize policies. My work has appeared in Management Science and Information Systems Research, and has received paper awards from INFORMS, WITS, ICIS, and DSI.

Over the past several years, I have collaborated closely with industry leaders to develop, implement, and evaluate large language models across exciting, high-stakes business environments. I have also partnered with multiple platforms to address their pain points by combining their business intuition with our rigorous “model thinking”. Additionally, leveraging unique, fine-grained data from these collaborations, I conduct empirical research to understand user behavior patterns and inform corresponding adjustments to platform policies and algorithms; several of these changes have persisted in production and continue to deliver substantial business value.