Mission and Vision
Wireless communication is the bedrock of modern civilization. From mobile connectivity to the Internet of Everything, every leap in communication technology has profoundly reshaped how societies collaborate and how knowledge flows. For decades, the evolution of wireless communication has been a story of relentless innovation. It is not only the underlying infrastructure of our digital world but also the core engine powering scientific discovery and industrial transformation.
At the Intelligent Communications Laboratory, we work at the frontier of communication science, committed to redefining what wireless systems can achieve. We believe that true breakthroughs come from deep understanding of fundamental principles and the courage to reimagine them. Our mission is to build wireless networks that are more intelligent, efficient, and reliable, laying a solid and advanced foundation for the rapidly evolving digital future.
Here, we bridge theory and application, today and tomorrow.
About the Supervisor
I received my B.S. and M.S. degrees (Hons.) in Communications and Information Engineering from Xidian University and my Ph.D. degree in Information Engineering from the Chinese University of Hong Kong (CUHK).
Dr. Yulin ShaoAssistant Professor Department of Electrical and Electronic Engineering The University of Hong Kong |  |
Previous Academic Positions held
Visiting Researcher
Imperial College London
Department of Electrical and Electronic Engineering
Assistant Professor
University of Macau
IOTSC State Key Laboratory
Lecturer (AP) in Information Processing
University of Exeter
Department of Engineering
Research Associate
Imperial College London
Department of Electrical and Electronic Engineering
Visiting Scholar
Massachusetts Institute of Technology
Claude E. Shannon Communication and Network Group
Research Assistant
Institute of Network Coding
Professional Services
Editor
IEEE Communications Magazine
Editor
IEEE Transactions on Wireless Communications
Editor
IEEE Transactions on Communications
Editor
IEEE Communications Letters
Session chair and TPC member
IEEE Communication Society flagship conferences
Guest Lecturer
5G Academy Italy
Invited Speaker
IEEE Information Theory Society Bangalore Chapter
Awards
Best Paper Award
IEEE Wireless Communications and Networking Conference (WCNC) 2024
Dubai, United Arab Emirates
Best Paper Award
IEEE International Conference on Communications (ICC) 2023
Rome, Italy
Best Poster Award
CIE Information Theory Society 2023
Nanjing, China
International Telecommunication Union (ITU) AI/ML in 5G Challenge 2021
Ranked third in problem "Federated learning for spatial reuse"
Nominated as a finalist in the Grand Challenge Finale
Global scholarship programme for research excellence
2019
Overseas research attachment programme
2018
Books
Selected Publications
Y. Shao. DEEP-IoT: Downlink-Enhanced Efficient-Power Internet of Things. IEEE Transactions on Wireless Communications, vol. 24, no. 2, pp. 1722-1736, 2025.
Y. Shao, C. Bian, L. Yang, Q. Yang, Z. Zhang, D. Gunduz. Point Cloud in the Air. IEEE Communications Magazine, vol. 36, no. 12, pp. 142-148, 2025.
Y. Shao, Q. Cao, and D. Gunduz. A Theory of Semantic Communication. IEEE Transactions on Mobile Computing, vol. 23, no. 12, pp. 12211-12228, 2024.
Y. Shao, Y. Cai, T. Wang, Z. Guo, P. Liu, J. Luo, D. Gunduz. Learning-based autonomous channel access in the presence of hidden terminals. IEEE Transactions on Mobile Computing, vol. 23, no. 5, pp. 3680-3695, 2024.
Y. Shao, S. Liew and D. Gunduz. Denoising noisy neural networks: A Bayesian approach with compensation. IEEE Transactions on Signal Processing, vol. 71, pp. 2460-2474, 2023.
Y. Shao, D. Gunduz and S. Liew. Bayesian over-the-air computation. IEEE Journal on Selected Areas in Communications, vol. 41, no. 3, pp. 589-606, 2023.
Y. Shao, D. Gunduz and S. Liew. Federated edge learning with misaligned over-the-air computation. IEEE Transactions on Wireless Communications, vol. 21, no. 6, pp. 3951-3964, 2022.
Y. Shao, D. Gunduz. Semantic communications with discrete-time analog transmission: a PAPR perspective. IEEE Wireless Communication Letter, 2022.
Y. Shao. Goal-oriented communication system redesign for wireless collaborative intelligence. IEEE Multimedia Communication Technical Committee – Frontiers, 2022.
Y. Shao, Q. Cao, S. Liew, and H. Chen. Partially observable minimum-age scheduling: the greedy policy. IEEE Transactions on Communications, vol. 70, no. 1, pp. 404-418, 2021.
Y. Shao, S. Liew, H. Chen, Y. Du. Flow sampling: network monitoring in large-scale software-defined IoT networks. IEEE Transactions on Communications, vol. 69, no. 9, pp. 6120-6133, 2021.
Y. Shao and S. Liew. Flexible subcarrier allocation for interleaved frequency division multiple access. IEEE Transactions on Wireless Communications, vol. 19, no. 11, pp. 7139-7152, 2020.
Y. Shao, A. Rezaee, S. Liew, and V. Chan. Significant sampling for shortest path routing: a deep reinforcement learning solution. IEEE Journal on Selected Areas in Communications, vol. 38, no. 10, pp. 2234–2248, 2020.
Y. Shao, S. Liew, and J. Liang. Sporadic ultra-time-critical crowd messaging in V2X. IEEE Transactions on Communications, vol. 69, no. 2, pp. 817-830, 2020.
Y. Shao, S. Liew, and T. Wang. AlphaSeq: sequence discovery with deep reinforcement learning. IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 9, pp. 3319–3333, 2019.
Y. Shao, S. Liew, and L. Lu. Asynchronous physical-layer network coding: symbol misalignment estimation and its effect on decoding. IEEE Transactions on Wireless Communications, vol. 16, no. 10, pp. 6881–6894, 2017.