Educational Background (in reverse chronological order)：

• [2006-2009]：[The Chinese University of Hong Kong] [Computer Science]  [Doctoral Degree]
• [2001-2004]：[Huazhong University of Science and Technology] [Control Theory and Control Engineering] [Master Degree]
• [1997-2001]：[Anhui University] [Automation] [Bachedor Degree]

Work Experience (in reverse chronological order)：

• [2022-Now]: [Fudan University] [School of Information Science and Engineering / College of Computational and Intelligent Innovation] [Professor]
• [2016-2021]: [Fudan University] [School of Information Science and Engineering] [Tenured Associate Professor]
• [2013-2015]: [Fudan University] [School of Information Science and Engineering] [Pre-Tenure Associate Professor]
• [2012-2013]: [The Chinese University of Hong Kong] [Department of Computer Science and Engineering] [Postdoctoral Fellow]
• [2007-2007]: [Intel China Research Center] [Senior Research Intern]
• [2009-2012]: [French National Institute for Research in Digital Science and Technology (INRIA)] [Postdoctoral Fellow]

XU Yuedong, Ph.D., is a Professor and Doctoral Supervisor at the College of Computer Science and Artificial Intelligence, Fudan University. He received his Ph.D. degree in Computer Science from The Chinese University of Hong Kong. His main research interests lie in machine learning systems. He has (previously) served as the principal investigator for four projects funded by the National Natural Science Foundation of China. He has published more than 30 papers in top-tier journals and conferences, including NSDI, ATC, MobiSys, MobiHoc, CoNEXT, INFOCOM, NeurIPS,  ICLR, ToN, and JSAC. He currently serves as an Associate Editor of **IEEE Transactions on Network and Science**. He sincerely welcomes research collaborations and outstanding student applications in foundation model training and inference systems as well as AI security.

Representative Publications：

[Zhiyi Yao, Pengbo Hu, Congcong Miao, and Xuya Jia, Zuning Liang, Yuedong Xu, Chunzhi He, Hao Lu, Mingzhuo Chen, Xiang Li], [Holmes: Localizing Irregularities in LLM Training with Mega-scale GPU Clusters], [USENIX NSDI], [2025]*

[Leyi Ye, Zhiyi Yao, Boliang Liu, Yuedong Xu*, Hui Wang, et al.] [A Self-updating Checkpointing and Fast Failure Recovery System for Distributed LLM Training], [IEEE Infocom], [2026]

[Zhiyi Yao, Zuning Liang, Yuedong Xu, and Jin Zhao, Jessie Hui Wang, Tong Li], [MemFerry: A Fast and Memory Efficient Offload Training Framework with Hybrid GPU Computation], [IEEE Infocom], [2025]*

[Ming Wen, Jiaqi Zhu, Yuedong Xu, and Yipeng Zhou, Dingding Han], [Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix], [NeurIPS], [2025]*

[Qingyang Duan, Chao Peng, Zeqin Wang, and Yuedong Xu, Shaoteng Liu, Jun Wu, John CS Lui], [Accelerating Distributed DNN Training via Transport Layer Scheduling], [IEEE TPDS], [2023]*

Research Awards：

[2025]: [Shanghai Program of Shanghai Academic/Technology Research Leader|上海市东方英才拔尖计划], [Shanghai Municipal Government], [First Completed Person]

[2022]: [Shanghai Science and Technology Progress Award|上海市科技进步一等奖], [Shanghai Municipal Government], [Fifth Completed Person]

[2019]: [Japan Okawa Foundation Research Grant|日本大川基金会研究助成奖], [The Okawa Foundation for Information and Telecommunications], [First Completed Person]