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!