Peichun Li

I am a second-year Ph.D. student in Computer Science at the University of Macau, advised by Prof. Yuan Wu. Prior to this, I earned my B.Eng. in Electronic Information Engineering and my M.Sc. in Control Science and Engineering, both under the supervision of Prof. Rong Yu at Guangdong University of Technology.

My research focuses on edge computing and distributed learning, with a particular interest in federated learning and efficient algorithms for AI applications.

For more details, please see my CV here.

I am working on cleaning up the code for my published paper. The code for some of my papers will be open-sourced soon.

📢News

• [May 11, 2025] Coauthored paper "Compression Meets Security: Low-Complexity Linear Collaborative Federated Learning with Enhanced Accuracy" has been accepted by IEEE TMC.
• [April 30, 2025] Coauthored paper "VimGeo: Efficient Cross-View Geo-Localization with Vision Mamba Architecture" has been accepted by IJCAI-25.

One More Thing

I would like to share some tools I have developed—they might be useful (or maybe not, but hopefully worth a look!).

• IEEE ComSoc Special Issue Tracker (Updated Automatically)
• IEEE BibTeX Modifier (期刊名&作者列表精简)
• Clock Zoo (时光动物园) - Grash the time

Publications [Full List]

AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices Peichun Li, Guoliang Cheng, Xumin Huang, Jiawen Kang, Rong Yu, Yuan Wu, Miao Pan INFOCOM 2023 / Paper / Code (Coming Soon)

FlexGen: Efficient On-Demand Generative AI Service with Flexible Diffusion Model in Mobile Edge Networks Peichun Li, Huanyu Dong, Liping Qian, Sheng Zhou, Yuan Wu IEEE TCCN (April 2025) / Paper / Code (Coming Soon)

Filling the Missing: Exploring Generative AI for Enhanced Federated Learning over Heterogeneous Mobile Edge Devices Peichun Li, Hanwen Zhang, Yuan Wu, Liping Qian, Rong Yu, Dusit Niyato, Xuemin Shen IEEE TMC (Oct. 2024) / Paper / Code (Coming Soon)

Snowball: Energy Efficient and Accurate Federated Learning with Coarse-to-Fine Compression over Heterogeneous Wireless Edge Devices Peichun Li, Guoliang Cheng, Xumin Huang, Jiawen Kang, Rong Yu, Yuan Wu, Miao Pan, Dusit Niyato IEEE TWC (Oct. 2023) / Paper

FedRelay: Federated Relay Learning for 6G Mobile Edge Intelligence Peichun Li, Yupei Zhong, Chaorui Zhang, Yuan Wu, Rong Yu IEEE TVT (April 2023) / Paper

FAST: Fidelity-Adjustable Semantic Transmission over Heterogeneous Wireless Networks Peichun Li, Guoliang Cheng, Jiawen Kang, Rong Yu, Liping Qian, Yuan Wu, Dusit Niyato IEEE ICC 2023 / Paper

FedGreen: Federated learning with fine-grained gradient compression for green mobile edge computing Peichun Li, Xumin Huang, Miao Pan, Rong Yu IEEE GLOBECOM 2021 / Paper