Haifeng Xu

Haifeng Xu is an Assistant Professor in the Department of Computer Science at the University of Chicago, directing the Strategic IntelliGence for Machine Agents (SIGMA) Lab. He also serves as a part-time scientist at Google Research. His research focuses on the economics of data and machine learning, particularly in multi-agent decision-making and market design for data and algorithms. He publishes widely in top venues like ICML, EC, AAAI, and IJCAI, and has received prestigious awards including the AI2050 Early Career Fellowship and the ACM SIGecom Dissertation Award (honorable mention).

Education: While not explicitly detailed in the provided text, his academic background includes a PhD in Computer Science from the University of Southern California, advised by Milind Tambe and Shaddin Dughmi. He was previously a postdoc at Harvard and held a position at the University of Virginia.

Research Interests: His work spans computational economics, AI strategy, and multi-agent systems. Key themes include designing algorithms for strategic environments, information markets, and understanding generative AI's impact on content ecosystems. Recent efforts explore human-AI competition, incentive-aware ML, and robust multi-agent learning.

Awards & Honors: AI2050 Fellow (2023), IJCAI Early Career Spotlight (2023), Google Faculty Award (2020), ACM SIGecom Dissertation Award (2019), IFAAMAS Distinguished Dissertation (2019), and multiple best paper awards at top conferences.

Advising & Grants: Supervises a dynamic group of PhD, master's, and undergraduate students, many of whom secure academic positions or industry roles. His research is funded by NSF, ARO, ONR, Schmidt Science, and Google Research. The SIGMA Lab emphasizes cutting-edge techniques in agentic AI and strategic intelligence.

Labs & Collaborations: Leads the SIGMA Lab, collaborating with institutions like Harvard, UVA, and Yale. Active in organizing workshops at EC, AAAI, and NeurIPS on topics like information economics and agentic AI.