Xianhao Chen (陈先浩) Assistant Professor Department of Electrical and Computer Engineering The University of Hong Kong Email: xcheneee [AT] hku.hk or xchen [AT] eee.hku.hk [Google Scholar]

About Me

I am an assistant professor at the Department of Electrical and Computer Engineering, the University of Hong Kong, where I lead the Wireless Information & Intelligence (WILL) lab. Prior to joining HKU, I received my Ph.D. in Electrical and Computer Engineering from the University of Florida in 2022, where I was supervised by Prof. Yuguang Fang. I earned my B.Eng. degree from Southwest Jiaotong University, Chengdu, China, in 2017 under the supervision of Prof. Gang Liu. My research interests include wireless networks, edge computing, and distributed machine learning.

Research Interests

Our group conducts research at the intersection of networking, communications, and machine learning. My primary research interest lies in machine learning in wireless and networked systems. We explore the fundamental trade-offs in communication networks and networked AI systems, as well as practical edge AI applications that address pressing societal challenges, including but not limited to:

• Networked Edge AI

  • Resource-constrained split/federated learning

  • Edge inference

  • Mobile edge computing

• Applications of Edge AI

  • On-device large language models (LLMs)

  • Edge AI for mental well-being

  • Mobile health

• Security and privacy in ML

  • Privacy-preserving split/federated learning

  • Security and privacy in LLMs

Selected Publications

Note: The full list can be found in Google Scholar.
An underlined first author denotes my supervised researcher/student.

Selected Papers

• [arXiv] SplitCom: Communication-efficient Split Federated Fine-tuning of LLMs via Temporal Compression
  T. Li, Y. Tang, Y. Song, C. Wu, X. Liu, P. Li, X. Chen*
  IEEE Transactions on Mobile Computing, Under review

• [arXiv] SpaceMoE: Towards Orbital General Intelligence with Distributed Mixture-of-Experts Inference
  Q. Chen, X. Chen*, M. Sheng, K. Huang
  IEEE Communications Magazine, Major revision

• [ICML] HO-SFL: Hybrid-Order Split Federated Learning with Backprop-Free Clients and Dimension-Free Aggregation
  Q. Chen, X. Wu, Y. Wang, X. Chen*
  International Conference on Machine Learning (ICML), 2026

• [arXiv] SiftMoE: Similarity-Aware Energy-Efficient Expert Selection for Wireless Distributed MoE Inference
  Q. Chen, X. Chen*, K. Huang*
  IEEE Transactions on Mobile Computing, under revision

• [arXiv] Rateless DeepJSCC for Broadcast Channels: a Rate-Distortion-Complexity Tradeoff
  Z. Qin, J. Huang, Z. Fei, H. Ding, Y. Shao, X. Chen*
  IEEE Transactions on Wireless Communications, major revision

• [TMC] SLIDE: Simultaneous Model Downloading and Inference at the Wireless Network Edge
  G. Qu, T. Li, Q. Chen, X. Chen*, S. Zhou
  IEEE Transactions on Mobile Computing, 2026

• [ToN] TrimCaching: Parameter-sharing Edge Caching for AI Model Downloading
  G. Qu, Z. Lin, Q. Chen, J. Li, F. Liu, X. Chen*, K. Huang,
  IEEE Transactions on Networking, 2026

• [ToN] LiFeChain: Lightweight Blockchain for Secure and Efficient Federated Lifelong Learning in IoT
  H. Chen, J. Deng, X. Wu, Z. Jiang, X. Zhang, X. Chen, E. Ngai, J. Liu,
  IEEE Transactions on Networking, 2026

• [TMC] Optimizing Split Federated Learning with Unstable Client Participation
  W. Wei, Z. Lin, X. Liu, H. Du, D. Niyato, X. Chen*
  IEEE Transactions on Mobile Computing, 2026

• [TMC] HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems
  Z. Lin, Z. Chen, X. Chen*, W. Ni, Y. Gao
  IEEE Transactions on Mobile Computing, 2026

• [TMC] Pipelining Split Learning in Multi-hop Edge Networks
  W. Wei, Z. Lin, T. Li, X. Li, X. Chen*
  IEEE Transactions on Mobile Computing, 2026

• [TMC] SlimCaching: Edge Caching of Mixture-of-Experts for Distributed Inference
  Q. Chen, X. Chen*, K. Huang*
  IEEE Transactions on Mobile Computing, 2026

• [arXiv] PartialLoading: User Scheduling and Bandwidth Allocation for Parameter-sharing Edge Inference
  G. Qu, Q. Chen, X. Chen*, K. Huang, Y. Fang
  IEEE Transactions on Mobile Computing, under revision

• [TMC] FedMeld: A Model-dispersal Federated Learning Framework for Space-ground Integrated Networks
  Q. Chen, X. Chen*, K. Huang*
  IEEE Transactions on Mobile Computing, 2025

• [Engineering] Space-ground Fluid AI for 6G Edge Intelligence
  Q. Chen, Z. Wang, X. Chen, J. Wen, D. Zhou, S. Ji, M. Sheng, K. Huang*
  Engineering, 2025

• [TMC] Hierarchical Split Federated Learning: Convergence Analysis and System Optimization
  Z. Lin, W. Wei, Z. Chen, C. Lam, X. Chen*, Y. Gao and J. Luo
  IEEE Transactions on Mobile Computing, 2025

• [COMST] Mobile Edge Intelligence for Large Language Models: A Contemporary Survey
  G. Qu, Q. Chen, Z. Lin, W. Wei, X. Chen*, K. Huang,
  IEEE Communications Surveys & Tutorials, 2025

• [ToN] AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks
  Z. Lin, G. Qu, W. Wei, X. Chen* and K. K. Leung
  IEEE/ACM Transactions on Networking, 2025

• [ICDCS] TrimCaching: Parameter-sharing AI Model Caching in Wireless Edge Networks
  G. Qu, Z. Lin, F. Liu, X. Chen*, K. Huang,
  IEEE International Conference on Distributed Computing Systems (ICDCS), 2024 (acceptance ratio: 21.9%)

• [TMC] FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks
  Z. Lin, Z. Chen, Z. Fang, X. Chen, X. Wang, and Y. Gao
  IEEE Transactions on Mobile Computing, 2024

• [arXiv] Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities
  Z. Lin, G. Qu, Q. Chen, X. Chen* and K. Huang
  IEEE Communications Magazine, 2025

• [COMST] Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities
  X. Chen, Y. Deng, H. Ding, G. Qu, H. Zhang, P. Li, and Y. Fang
  IEEE Communications Surveys & Tutorials, 2024

• [TMC] Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks
  Z. Lin, G. Zhu, Y. Deng, X. Chen*, Y. Gao, K. Huang and Y. Fang
  IEEE Transactions on Mobile Computing, 2024

• [WCM] Split Learning in 6G Edge Networks
  Z. Lin, G. Qu, X. Chen* and K. Huang
  IEEE Wireless Communications, 2024

• [TMC] LiteChain: A Lightweight Blockchain for Verifiable and Scalable Federated Learning in Massive Edge Networks
  H. Chen, R. Zhou, Y. Chan, Z. Jiang, X. Chen and E. Ngai,
  IEEE Transactions on Mobile Computing, 2024

• [ToN] End-to-End Service Auction: A General Double Auction Mechanism for Edge Computing Services
  X. Chen, G. Zhu, H. Ding, L. Zhang, H. Zhang, and Y. Fang,
  IEEE/ACM Transactions on Networking, 2022

• [TWC] Federated Learning over Multi-Hop Wireless Networks with In-Network Aggregation
  X. Chen, G. Zhu, Y. Deng, and Y. Fang,
  IEEE Transactions on Wireless Communications, 2022

• [WCM] Actions at the Edge: Jointly Optimizing the Resources in Multi-access Edge Computing
  Y. Deng, X. Chen*, G. Zhu, Y. Fang, Z. Chen, and X. Deng,
  IEEE Wireless Communications, 2022

• [WCM] From Resource Auction to Service Auction: An Auction Paradigm Shift in Wireless Networks
  X. Chen, Y. Deng, G. Zhu, D. Wang, and Y. Fang,
  IEEE Wireless Communications, 2022

• [TMC] Timeliness-Aware Incentive Mechanism for Vehicular Crowdsourcing in Smart Cities
  X. Chen, L. Zhang, Y. Pang, B. Lin, and Y. Fang,
  IEEE Transactions on Mobile Computing, 2022

• [TNSE] Age-Stratified COVID-19 Spread Analysis and Vaccination: A Multitype Random Network Approach
  X. Chen, G. Zhu, L. Zhang, Y. Fang, L. Guo, and X. Chen,
  IEEE Transactions on Network Science and Engineering, 2021

• [WCM] When Full Duplex Wireless Meets Non-Orthogonal Multiple Access: Opportunities and Challenges
  X. Chen, G. Liu, Z. Ma, X. Zhang, P. Fan, S. Chen, and F. R. Yu,
  IEEE Wireless Communications, 2019

• [TWC] Optimal Power Allocations for Non-Orthogonal Multiple Access Over 5G Full/Half-Duplex Relaying Mobile Wireless Networks
  X. Chen, G. Liu, Z. Ma, X. Zhang, W. Xu, and P. Fan,
  IEEE Transactions on Wireless Communications, 2018

Recognitions

• Early Career Award, Research Grants Council (RGC) of Hong Kong, 2024

• IEEE ICCC Best Paper Award, 2023

• ECE Graduate Excellence Award in Research, the University of Florida, 2022

Selected Professional Services

• Editor:

  • IEEE Transactions on Networking

  • IEEE Transactions on Wireless Communications

  • IEEE Transactions on Vehicular Technology

  • ACM Computing Surveys

• TPC Member:

  • MobiHoc'26, INFOCOM'27, GLOBECOM'23–26, ICC'25, SEC'26, IWQoS'24

• Track/Symposium Chair:

  • Track Chair of IEEE VTC-Fall, 2025

  • System Demo Chair of IEEE/CIC ICCC, 2025

Teaching

• ELEC8501: The Fourier Transform and Its Applications, Spring 2026

• ELEC3255: Control Systems II, HKU, Fall 2023, Spring 2024, Spring 2025

• ELEC8002: Advanced Topics in Networking, HKU, Spring 2023

• ELEC4256: Wireless Networking in the Era of Machine Learning, HKU, Fall 2023, Fall 2024