Xiaohu Wu

613 Mingguang Building, 10 Xitucheng Road

Haidian District, Beijing, China

I am an Associate Professor at Beijing University of Posts and Telecommunications, Beijing, China. I received a PhD degree from Telecom Paris, a school of Institut Polytechnique de Paris, France, under the supervision of Prof. Patrick Loiseau (Inria). During my doctoral studies, I was a visiting student at the University of California at Berkeley, United States, working with Prof. Jean Walrand. After completing my PhD, I was also a Research Fellow at Nanyang Technological University, Singapore, supervised by Prof. Han Yu.

My current research focuses on federated learning and its interplay with foundation models. I have published in leading venues spaning machine/federated learning, mathematical modeling and optimization, and computing systems, including NeurIPS, ICML, ICCV, AAAI, IJCAI, Artificial Intelligence, European Journal of Operational Research, IEEE Transactions/Journals (e.g., TBD, TPDS, TSC, JBHI), ACM Transactions (e.g., ToMPECS), and Performance Evaluation. In 2024, I received an outstanding student paper award at a workshop of NeurIPS 2024.

news

Jun 26, 2025	Our paper on personalized federated learning is accepted to ICCV 2025 (CCF A), in collaboration with Dr. Qiqi Liu, Prof. Yaochu Jin, Dr. Lingjuan Lyu, and Prof. Han Yu.
May 02, 2025	Two papers on collaborative federated learning and vision language models are accepted to ICML 2025 (CCF A), in collaboration with Prof. Han Yu, Prof. Qicheng Lao, Dr. Tiantian He, Dr. Qiqi Liu, Prof. Yew-Soon Ong, and Prof. Yaochu Jin.
Mar 05, 2025	We are organizing the International Workshop on Federated Learning with Generative AI at IJCAI 2025 (FedGenAI-IJCAI'25), together with Prof. Jindong Wang, Dr. Lingjuan Lyu, Dr. Dimitrios Dimitriadis, and Prof. Han Yu.
Jan 26, 2025	Our paper on AI for decision-making is accepted to IEEE TSC (CCF A), in collaboration with Prof. Han Yu, Prof. Giuliano Casale, and Prof. Guanyu Gao.

selected publications (* indicates my student)

ICML

Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning

Mengmeng Chen^*†, Xiaohu Wu^†, Qiqi Liu, Tiantian He, Yew-Soon Ong, Yaochu Jin, Qicheng Lao, and Han Yu

The 42nd International Conference on Machine Learning, 2025

CCF A, CORE A* Bib

@article{chenvoronoi,
  title = {Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning},
  author = {Chen, Mengmeng and Wu, Xiaohu and Liu, Qiqi and He, Tiantian and Ong, Yew-Soon and Jin, Yaochu and Lao, Qicheng and Yu, Han},
  journal = {The 42nd International Conference on Machine Learning},
  year = {2025},
  volume = {},
  number = {},
  pages = {},
  publisher = {PMLR},
}

NeurIPS

Free-rider and conflict aware collaboration formation for cross-silo federated learning

Mengmeng Chen^*, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew Soon Ong, Qiqi Liu, Qicheng Lao, and Han Yu

Advances in Neural Information Processing Systems, 2024

CCF A, CORE A* Bib

@article{chen2024free,
  title = {Free-rider and conflict aware collaboration formation for cross-silo federated learning},
  author = {Chen, Mengmeng and Wu, Xiaohu and Tang, Xiaoli and He, Tiantian and Ong, Yew Soon and Liu, Qiqi and Lao, Qicheng and Yu, Han},
  journal = {Advances in Neural Information Processing Systems},
  volume = {37},
  pages = {54974--55004},
  year = {2024},
  number = {},
  publisher = {Curran Associates Inc.},
}

AAAI

Fedcompetitors: Harmonious collaboration in federated learning with competing participants

Shanli Tan^*†, Hao Cheng^†, Xiaohu Wu^†, Han Yu^†, Tiantian He, Yew Soon Ong, Chongjun Wang, and Xiaofeng Tao

Proceedings of the AAAI Conference on Artificial Intelligence, 2024

CCF A, CORE A* Bib

@article{Tan24a,
  title = {Fedcompetitors: Harmonious collaboration in federated learning with competing participants},
  author = {Tan, Shanli and Cheng, Hao and Wu, Xiaohu and Yu, Han and He, Tiantian and Ong, Yew Soon and Wang, Chongjun and Tao, Xiaofeng},
  journal = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {38},
  number = {14},
  pages = {15231--15239},
  year = {2024},
  publisher = {},
}