معرفی
Yuan Yuan is an Assistant Professor of Business Analytics at the University of California, Davis Graduate School of Management. He is currently on leave at OPENAI as a researcher in AI safety. Previously, he served as an assistant professor at Purdue University in the Management Information Systems area. Yuan holds a Ph.D. from the Institute for Data, Systems, and Society (IDSS) at the Massachusetts Institute of Technology and earned dual Bachelor's degrees with honors in Computer Science and Economics from Tsinghua University.
- Ph.D., Social & Engineering Systems, MIT
- Bachelor, Computer Science & Economics, Tsinghua University
As a computational social scientist, Yuan Yuan specializes in social and organizational networks, leveraging big data and advanced computational methodologies including machine learning and causal inference to study network formation, dynamics, social contagion, and prosocial behavior. His research extends to experimentation, where he develops computational techniques to address challenges in online field experiments (A/B testing), particularly concerning network interference, budget constraints, and long-term experiments. More recently, he has been exploring the capabilities of Large Language Models in advancing social science studies. His interdisciplinary research spans engineering, social science, and business domains, with applications in organizational behavior, public health, and technology management.
Yuan's research portfolio demonstrates a consistent focus on computational approaches to understanding network phenomena. His most recent publications show a growing interest in applying AI and machine learning techniques to traditional social science questions, particularly examining how Large Language Models can be used to study social behavior and network formation. His work bridges theoretical network science with practical applications in organizational settings, with strong industry connections to technology companies. His publications span top-tier venues including PNAS, Nature Communications, Management Science, and leading computer science conferences like WWW and EC.
Yuan actively collaborates with industry partners, working closely with companies like Microsoft and Meta to explore topics in networks and A/B testing. His research often emerges from these industry collaborations, ensuring practical relevance alongside academic rigor. He has served as a visiting researcher at Microsoft Office of Applied Research (part-time since summer 2022) and was previously a research intern at Facebook Core Data Science (now Meta Central Applied Science) in summer 2020.
Yuan contributes to the academic community through service as a Technical Program Committee member for the MIT Conference on Digital Experimentation (2019-2021), reviewer for prestigious journals and conferences including Management Science, MIS Quarterly, and WWW, and organizer of academic workshops such as SICSS Beijing 2021 and the WINE Experimentation Workshop 2021. He has been invited to present his work at leading institutions worldwide including MIT, Stanford, Harvard, Oxford, and Tsinghua University.
