Boyi Liu | 刘博一 Ph.D. student School of Computer Science and Engineering, Beihang University Department of Data Science, City University of Hong Kong [GitHub] [DBLP] [Google Scholar] Email: boyliu [at] buaa [dot] edu [dot] cn

Biography

Boyi Liu is currently a third year Ph.D. student at the Beihang University (BUAA), under the supervision of Prof. Yongxin Tong. He is also a joint Ph.D student at the City University of Hong Kong (CityUHK), co-supervised by Prof. Zimu Zhou. Currently he is based at City University of Hong Kong. His research interests include:

• Federated LLM (Fine-tuning, RAG, et al.)

• On-device Machine Learning

• Agentic LLM

Publications

1. CAFEDistill: Learning Personalized and Dynamic Models through Federated Early-Exit Network Distillation
   Boyi Liu, Zimu Zhou, Yongxin Tong
   Preprint, 2026
   [Paper] [Code]
2. FedMosaic: Federated Retrieval-Augmented Generation via Parametric Adapters
   Zhilin Liang, Yuxiang Wang, Zimu Zhou, Hainan Zhang, Boyi Liu, Yongxin Tong
   Preprint, 2026
   [Paper] [Code]
3. Towards Asynchronous Client Collaboration in Personalized Federated Learning
   Boyi Liu, Zimu Zhou, Pengfei Gao, Shuo Kang, Yongxin Tong
   IEEE International Conference on Computer Communications (INFOCOM), 2026 (CCF-A)
   [Paper] [Code]
4. Harnessing Asynchrony to Balance Modalities in Multi-Modal Federated Learning
   Yiming Ma, Boyi Liu, Zimu Zhou, Yanfeng Wang, Yongxin Tong
   International Conference on Database Systems for Advanced Applications (DASFAA), 2026 (CCF-B)
   [Paper]
5. Poster: Asynchronous Federated Learning Library and Benchmark with AFL-Lib
   Boyi Liu, Shuyuan Li, Zimu Zhou, Shuo Kang, Yiming Ma, Yongxin Tong
   ACM Annual International Conference on Mobile Computing and Networking (MobiCom), 2025 (CCF-A)
   [Paper] [Code] [Poster]
6. FedAIMS: Personalized Federated Learning with Adaptive Intermediate Supervision
   Shuyuan Li, Boyi Liu, Zimu Zhou, Jin Dong
   Frontiers of Computer Science (FCS), 2025 (CCF-B)
   [Paper] [Code]
7. DarkDistill: Difficulty-Aligned Federated Early-Exit Network Training on Heterogeneous Devices
   Lehao Qu, Shuyuan Li, Zimu Zhou, Boyi Liu, Yi Xu, Yongxin Tong
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025 (CCF-A)
   [Paper] [Slides] [Poster]
8. Factor for Agent (FAgent): Collaborative Learning of Large and Small Language Models
   Shuyuan Li, Yongxin Tong, Qiang Yang, Zimu Zhou, Boyi Liu
   Computing Magazine of the CCF (CCCF), 2025
   [Paper]
9. CASA: Clustered Federated Learning with Asynchronous Clients
   Boyi Liu, Yiming Ma, Zimu Zhou, Yexuan Shi, Shuyuan Li, Yongxin Tong
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024 (CCF-A)
   [Paper] [Slides] [Poster]
10. Federated Computing: Query, Learning, and Beyond
    Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Boyi Liu, Yexuan Shi, Shuyuan Li, Ke Xu, Weifeng Lv
    IEEE Data Engineering Bulletin (DEB), 2023
    [Paper]
11. Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction
    Ruixing Zhang, Liangzhe Han, Boyi Liu, Jiayuan Zeng, Leilei Sun
    International Joint Conference on Artificial Intelligence (IJCAI), 2022 (CCF-A)
    [Paper] [Code]

News

• [2026/01] Two papers for early-exit network training and federated retrieval-augmented generation are preprint on arXiv now.

• [2026/01] One paper for multimodal federated learning was accepted by DASFAA 2026.

• [2025/12] One paper for personalized federated learning was accepted by INFOCOM 2026.

• [2025/08] One poster paper for asynchronous federated learning was accepted by MobiCom 2025.

• [2025/07] One paper for personalized federated learning was accepted by Frontiers of Computer Science (FCS).

• [2025/05] One paper for model heterogeneous federated learning was accepted by KDD 2025.

Academic Services

• Reviewer for Journals: IEEE TKDE, IEEE TBD, ACM IMWUT

• Reviewer for Conferences: ICLR, ICML, KDD, NeurIPS

Educations

• Joint Ph.D. Department of Data Science, City University of Hong Kong, 2024 - Present

• Ph.D. School of Computer Science and Engineering, Beihang University, 2023 - Present

• B.E. School of Computer Science and Engineering, Beihang University, 2019 - 2023