(Note: A more frequently updated homepage can be found at https://lynshao.github.io/Lab.github.io/)


Assistant Professor, State Key Laboratory of Internet of Things for Smart City, University of Macau.

CONTACT (联系方式):

 University of Macau: ylshao@um.edu.mo

 Imperial College London: y.shao@imperial.ac.uk

 IEEE Communication Society: ylshao@ieee.org


 Ph.D. in Information Engineering, Chinese University of Hong Kong (Aug. 2016 – Dec. 2020).

 B.E. and M.E. (Hons.) in Communication and Information Systems, Xidian University (Sept. 2009 – Jan. 2016).


 Imperial College London (Nov. 2022 – present)

Visiting Researcher at the Department of Electrical and Electronic Engineering.

 University of Exeter (Nov. 2022 – Aug. 2023)

Lecturer (assistant professor) in Information Processing at the Department of Engineering.

 Imperial College London (Jan. 2021 – Nov. 2022)

Research Associate at the Department of Electrical and Electronic Engineering.

 Massachusetts Institute of Technology (Sept. 2018 – Mar. 2019)

Visiting Scholar at the Claude E. Shannon Communication and Network Group.

 Institute of Network Coding (Mar. 2015 – July 2016)

Research Assistant at the Institute of Network Coding.


• Fundamentals of wireless communications.
Tools: signal processing, matrix theory, real analysis, statistical inference.

• Data science and machine learning.
Tools: deep learning, variational Bayesian methods, reinforcement learning, graph signal processing.

• Networking and stochastic control.
Tools: Markov decision process theory, reinforcement learning, optimization.

AWARDS (所获奖项):

• IEEE International Conference on Communications 2023, Best Paper Award.

• International Telecommunication Union (ITU) AI/ML in 5G Challenge 2021, ranked third in problem “Federated learning for spatial reuse” and nominated as a finalist in the Grand Challenge Finale.

• Global scholarship programme for research excellence 2019.

 Oversea research attachment programme 2018.


 IEEE Communications Magazine, Series Editor for the track “Artificial Intelligence and Data Science for Communications”.

Session chair and technical program committee (TPC) member for IEEE flagship conferences.


Y. Shao, E. Ozfatura, A. Perotti, B. Popovic, and D. Gunduz. AttentionCode: ultra-reliable feedback codes for short-packet communications, IEEE Transactions on Communications, 2023.

 Y. Shao, S. Liew and D. Gunduz. Denoising noisy neural networks: A Bayesian approach with compensation, IEEE Transactions on Signal Processing, 2023.

 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, 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.



Los Angeles