- Sept. 2025, committee member of IEEE Hong Kong 6G Wireless Summit
- May 2025, paper 'Edge Large AI Models: Collaborative Deployment and IoT Applications' accepted by IEEE IoT. Mag.
- May 2025, paper 'Edge Large AI Models: Revolutionizing 6G Networks' accepted by IEEE Commun. Mag.
- Mar. 2025, paper 'Microservice Migration in Hybrid Satellite-Terrestrial Networks for Autonomous Vehicles' accepted by J. Commun. Info. Netw. and selected for the cover article
- Mar. 2025, paper 'Learning to Beamform for Integrated Sensing and Communication: A Graph Neural Network with Implicit Projection Approach' accepted by IEEE Trans. Wireless Commun.
- Jan. 2025, paper 'Federated Fine-Tuning for Pre-Trained Foundation Models Over Wireless Networks' accepted by IEEE Trans. Wireless Commun.
- Dec. 2024, attended GLOBECOM 2024, Cape Town, SA
- Sept. 2024, attended IEEE Hong Kong 6G Wireless Summit
- Sept. 2024, paper 'Over-the-air Federated Graph Learning' accepted by IEEE Trans. Wireless Commun.
- Aug. 2024, paper 'Graph Attention-based MADRL for Access Control and Resource Allocation in Wireless Networked Control Systems' accepted by IEEE Trans. Wireless Commun.
- Aug. 2024, paper 'Federated Low-Rank Adaptation for Large Language Model Fine-Tuning Over Wireless Networks' accepted by GLOBECOM 2024
- Mar. 2024, joined HKUST as a post-doctoral fellow, working with Prof. Khaled B. Letaief
- Nov. 2023, passed thesis defense
- Nov. 2022, started visiting Oulu University as a visiting doctoral researcher, working with Prof. Mehdi Bennis
Research Experience
- Research Assistant Professor at Dept. ECE, Hong Kong University of Science and Technology (HKUST), currently working with Prof. Khaled B. Letaief
- Post-doctoral fellow at HKUST, starting from Mar. 2024, working with Prof. Khaled B. Letaief
Education
- Ph.D. from the University of Chinese Academy of Sciences (ShanghaiTech University), 2024, co-supervised by Prof. Yong Zhou
- B.Sc. from Wuhan University of Technology, 2018
- Visiting doctoral researcher at CWC, Oulu University, from Nov. 2022 to Oct. 2023, supervised by Prof. Mehdi Bennis
Background
Research areas include edge intelligence, edge large AI model, federated learning, and network optimization.