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 Computing and Artificial Intelligence
Curriculum Vitae (2026.01)

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Renzhe Xu is a tenure-track assistant professor at Institute for Theoretical Computer Science, School of Computing and Artificial Intelligence, Shanghai University of Finance and Economics. He received his Ph.D. in Computer Science from Tsinghua University in 2024, advised by Prof. Peng Cui and Prof. Bo Li, and his B.E. in Computer Science from Tsinghua University in 2019. During the Spring semester of 2024, he visited the Theory Group at the Department of Computer Science, Duke University, working with Prof. Kamesh Munagala. He received the Best Paper Award at WINE 2025.

His research develops economic and algorithmic foundations for AI platforms and digital markets. He studies how strategic agents such as users, creators, and learning systems interact, compete, and respond to algorithmic incentives, and how platforms can be designed to achieve efficiency, robustness, and fairness. His work spans recommendation systems [KDD’26, KDD’25, ICML’23], data markets [ICML’25], and online platforms [WINE’25, WWW’22]. He also studies the reliability and trustworthiness of machine learning, including generalization [NMI’24, ICML’22] and algorithmic fairness [KDD’20]. His long-term goal is to build principled and socially responsible foundations for large-scale AI systems deployed in the real world.

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. † indicates corresponding authors.

  1. Shaohua Fan*, Renzhe Xu*, Qian Dong*, Yue He, Cheng Chang, Peng Cui
    Nature Machine Intelligence (NMI 2024)
  1. Kang Wang, Renzhe Xu†, Bo Li
    In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD 2026)
  2. (α-β) Kamesh Munagala, Yiheng Shen, Renzhe Xu
    In International Conference on Web and Internet Economics (WINE 2025)
    Best Paper Award
  3. Renzhe Xu, Kang Wang, Bo Li
    In Proceedings of the 42th International Conference on Machine Learning (ICML 2025)
  4. Renzhe Xu*, Haotian Wang*, Xingxuan Zhang, Bo Li, Peng Cui
    In Proceedings of the 40th International Conference on Machine Learning (ICML 2023)

Teaching

  • Spring 2025: Algorithm Design and Complexity Analysis
  • Fall 2024-2025: Computer Programming (Economics)
  • Fall 2024-2025: 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.