Renzhe Xu 徐韧喆
Assistant Professor, Shanghai University of Finance and Economics
Email: xurenzhe [at] sufe [dot] edu [dot] cn
Office: 521, School of Information Management and Engineering
Curriculum Vitae (2025.05)
Hi! I am a tenure-track assistant professor at Institute for Theoretical Computer Science, School of Computing and Artificial Intelligence, Shanghai University of Finance and Economics. I obtained my Ph.D. at Computer Science and Technology at Tsinghua University, advised by Prof. Peng Cui and Prof. Bo Li, and my B.E. at Computer Science and Technology at Tsinghua University. During the Spring Semester of 2024, I visited the Theory Group at the Department of Computer Science, Duke University, working with Prof. Kamesh Munagala.
My research lies at the intersection of machine learning and algorithmic game theory, with a focus on understanding and designing complex ML-driven systems involving strategic interactions among agents. I am particularly interested in characterizing agents’ behaviors and equilibria in environments such as recommendation systems [KDD’25, ICML’23], data markets [ICML’25], and online platforms [ArXiv’24, WWW’22]. Beyond market design, I am also passionate about the trustworthiness of machine learning algorithms, with work on their generalization capabilities [NMI’24, ICML’22] and algorithmic fairness [KDD’20]. My ultimate goal is to build principled, robust, and socially aware ML systems for real-world decision-making.
I am happy to host remote graduate / undergraduate visitors and actively looking for Ph.D. students. If you are interested, please contact me!
Selected Publications
The full list of publications can be found in the research page.
* indicates equal contributions. (α-β) indicates alphabetical order.
- In Proceedings of the 42th International Conference on Machine Learning (ICML 2025)
- Nature Machine Intelligence (NMI 2024)
- arXiv preprint arXiv:2406.06023
- In Proceedings of the 40th International Conference on Machine Learning (ICML 2023)
- In Proceedings of the 39th International Conference on Machine Learning (ICML 2022)
- In Proceedings of the ACM Web Conference 2022 (WWW 2022)Scientific AmericanMontreal AI Ethics Institute
Teaching
- 2025 Spring: Algorithm Design and Complexity Analysis
- 2024 Fall: Computer Programming (Economics)
- 2024 Fall: Optimization theory and algorithm II
Services
- Top reviewer: NeurIPS 2022 (10%)
- Conference reviewer / Program committee: ICML (2022-2025), ICLR (2023-2025), NeurIPS (2022-2025), UAI (2022-2024), CVPR (2022-2025), ICCV (2023), ECCV (2022, 2024), KDD (2022-2025), WWW (2024), FAccT (2024), CLeaR (2024), AAAI (2022)
- Journal reviewer: IEEE Transactions on Mobile Computing, IEEE Transactions on Control Systems Technology, Games
- Contributor of IEEE Standards Association 3198 Development Group - Standard for Evaluation Method of Machine Learning Fairness
Acknowledgments: based on Jekyll with al-folio theme by Maruan Al-Shedivat.