About

Expanding Intelligence. Advancing Humanity.

I am a Postdoctoral Research Fellow affiliated with the Center for Science of Science & Innovation at Kellogg, led by Dashun Wang. I am also affiliated with the Northwestern Innovation Institute (NII) and the Ryan Institute on Complexity. We’re building unique platforms and exciting research to cultivate intelligence, connect it, and maximize its impact. More on our “startup” effort soon.

I got my PhD in Information Systems at the Michael G. Foster School of Business, University of Washington (2026). I was 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 (2016-2021).

I study the economics of human–AI and AI–AI interactions to augment human intelligence, improve well-being, and enhance social welfare in high-stakes domains. My current research spans cultivating intelligence through education, expanding its frontiers through science, and translating it into technological innovation and work. I examine these interactions at the individual, market, and societal levels, introducing empirical insights into design principles for AI systems, human–AI collaboration, market mechanisms, and public policy.

I take a multidisciplinary approach, combining economic tools (field experiments, stylized models, structural estimation) with AI methods (primarily 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 leading institutions to develop, implement, and evaluate algorithms within high-stakes environments. I have also partnered with multiple platforms to address critical pain points by integrating their business intuition with rigorous data analysis. Several of the interventions I proposed have been integrated into production, where they continue to deliver substantial value.

I enjoy diving deep into data patterns and modeling techniques so that I understand the details firsthand. I also believe good science comes from quiet time and deep thinking (slow science with fast tests) rather than from shallow discussion. Protecting that time means two commitments:

1. I keep new collaborations to a small number each year. When I take on a new project, I look for three things: a fit with the topics above, relevance to important sectors, and collaborators who genuinely enjoy thinking deeply.
2. I avoid meetings that have no clear agenda, or where participants haven’t thought through the questions beforehand. For the same reason, I do not use messaging apps to discuss research.

For professional contact, please email cedric.x.xu@gmail.com. (For communication within NU, please search “Xingchen Xu” in the email system.)

Note: Only the papers listed on this website represent my views.

Updated: 2026/10