Academic Qualifications

Ph.D. in Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong

B.Eng. in Information and Communication Engineering, Zhejiang University, China

Teaching Areas

• Computer Networks I/II

• Computer Networks Laboratory I/II

• Communication Networks

• Special Topics in Networking and Communication

• Introduction to Artificial Intelligence

Research Areas

• Wireless Communications and Networking

• Low-altitude Wireless Networking

• Mobile Edge Intelligence

• Integrated AI, Sensing, and Communication

• Distributed and Federated Learning

• Smart Internet of Things

Openings

I am looking for Ph.D. and M.Sc. students who are passionate about advancing research in the above areas to join my group.

Professional Services

• Editor, IEEE Wireless Communications Letters

• Associate Editor, IEEE Transactions on Mobile Computing

• Associate Editor, Journal on Wireless Communications and Networking

• Associate Editor, HKIE Transactions

Working Experience

• Jan. 2025 ~ present, Assistant Professor, School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau

• Jul. 2023 ~ Jan. 2025, Research Assistant Professor, Department of Electrical and Electronic Engineering, Hong Kong Polytechnic University, Hong Kong

• May 2020 ~ Jun. 2023, Research Assistant Professor, Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong

• May 2019 ~ Apr. 2020, Senior Researcher, Theory Lab, 2012 Labs, Huawei Tech. Investment Co. Ltd., Hong Kong

• Oct. 2017 ~ Apr. 2019, Senior Engineer/Lead Engineer, Communications Technologies Division, Hong Kong Applied Science and Technology Research Institute Co. Ltd., Hong Kong

Academic Publication

Journal Articles (Past Five Years)

1. N. Zhang, Q. Hu, D. Wen, Y. Mao, T.-M. Ma, G. Yu, and W. Wang, “Integrated sensing-communication-computation based online federated learning with limited cache in OFDM systems,” IEEE Trans. Cogn. Commun. Netw., vol. 12, pp. 5578-5594, Jan. 2026.

2. X. Ye, Y. Mao, X. Yu, and L. Fu, “Joint MCS adaptation and beamforming design for multi-user MISO systems: A contrast deep reinforcement learning approach,” IEEE Internet Things J., vol. 12, no. 23, pp. 50852-50867, Dec. 2025.

3. X. Ye, Y. Mao, X. Yu, S. Sun, L. Fu, and J. Xu, “Integrated sensing and communications for low-altitude economy: A deep reinforcement learning approach,” IEEE Trans. Wireless Commun., vol. 25, pp. 351-367, Jan. 2026.

4. Y. Zhang, Y. Mao, H. Wang, Z. Yu, S. Guo, J. Zhang, L. Wang, and B. Guo, “Orchestrating joint offloading and scheduling for low-latency edge SLAM,” IEEE Trans. Mob. Comput., vol. 24, no. 8, pp. 6901-6917, Aug. 2025.

5. X. Ye, Y. Mao, X. Yu, and L. Fu, “Intelligent omni-surface-aided integrated sensing and communications based on deep reinforcement learning with knowledge transfer,” IEEE Trans. Wireless Commun., vol. 24, no. 5, 4344-4360, May 2025.

6. Z. Fu, J. Liu, Y. Mao, L. Qu, L. Xie, and X. Wang, “Energy-efficient UAV-assisted federated learning: Trajectory optimization, device scheduling, and resource management,” IEEE Trans. Netw. Service Manag., vol. 22, no. 2, pp. 974-988, Apr. 2025.

7. W. Zhuang, X. He, Y. Mao, and J. Liu, “UAV-enabled wireless networks for integrated sensing and learning-oriented communication,” IEEE Wireless Commun. Lett., vol. 14, no. 2, pp. 340-344, Feb. 2025.

8. L. Qu, Y. Mao, S. Song, and C. Y. Tsui, “Energy-efficient channel decoding for wireless federated learning: Convergence analysis and adaptive design,” IEEE Trans. Wireless Commun., vol. 23, no. 11, pp. 17222-17235, Nov. 2024.

9. Y. Mao, X. Yu, K. Huang, Y.-J. A. Zhang, and J. Zhang, “Green edge AI: A contemporary survey,” Proc. IEEE, vol. 112, no. 7, pp. 880-911, Jul. 2024.

10. Z. Li, Z. Lin, J. Shao, Y. Mao, and J. Zhang, “FedCiR: Client-invariant representation learning for federated non-IID features,” IEEE Trans. Mob. Comput., vol. 23, no. 11, pp. 10509-10522, Nov. 2024.

11. Z. Li, Y. Sun, J. Shao, Y. Mao, J. H. Wang, and J. Zhang, “Feature matching data synthesis for non-IID federated learning,” IEEE Trans. Mob. Comput., vol. 23, no. 10, pp. 9352-9367, Oct. 2024.

12. Y. Sun, Z. Lin, Y. Mao, S. Jin, and J. Zhang, “Channel and gradient-importance aware device scheduling for over-the-air federated learning,” IEEE Trans. Wireless Commun., vol. 23, no. 7, pp. 6905-6920, Jul. 2024.

13. W. Zhuang, Y. Mao, H. He, L. Xie, S.H. Song, Y. Ge, and Z. Ding, “Approximate message passing-enhanced graph neural network for OTFS data detection,” IEEE Wireless Commun. Lett., vol. 13, no. 7, pp. 1913-1917, Jul. 2024.

14. Y. Sun, Y. Mao, and J. Zhang, “MimiC: Combating client dropouts in federated learning by mimicking central updates,” IEEE Trans. Mob. Comput., vol. 23, no. 7, pp. 7572-7584, Jul. 2024.

15. Y. Sun, J. Shao, Y. Mao, S. Li, and J. Zhang, “Stochastic coded federated learning: Theoretical analysis and incentive mechanism design,” IEEE Trans. Wireless Commun., vol. 23, no. 6, pp. 6623-6638, Jun. 2024.

16. X. Bian, Y. Mao, and J. Zhang, “Grant-free massive random access with retransmission: Receiver optimization and performance analysis,” IEEE Trans. Commun., vol. 72, no. 2, pp. 786-800, Feb. 2024.

17. X. Bian, Y. Mao, and J. Zhang, “Joint activity detection, channel estimation, and data decoding for grant-free massive random access,” IEEE Internet Things. J., vol. 10, no. 16, pp. 14042-14057, Aug. 2023.

18. Y. Sun, J. Shao, Y. Mao, J. H. Wang, and J. Zhang, “Semi-decentralized federated edge learning with data and device heterogeneity,” IEEE Trans. Netw. Service Manag., vol. 20, no. 2, pp. 1487-1501, Jun. 2023.

19. J. Shao, Y. Mao, and J. Zhang, “Task-oriented communication for multi-device cooperative inference,” IEEE Trans. Wireless Commun., vol. 22, no. 1, pp. 73-87, Jan. 2023.

20. R. Dong, Y. Mao, and J. Zhang, “Resource-constrained edge AI with early exit prediction,” J. Commun. Inf. Netw., vol. 7, no. 2, pp. 122-134, Jun. 2022.

21. J. Shao, Y. Mao, and J. Zhang, “Learning task-oriented communication for edge inference: An information bottleneck approach,” IEEE J. Sel. Areas Commun., vol. 40, no. 1, pp. 197-211, Jan. 2022.

Research Grants

• 2026.04 -- Now     PI, Research on movable antenna-empowered federated edge intelligence (MUST Faculty Research Grant)

• 2022.10 -- 2025.4    Co-I, Channel state information-learning-based passenger counting system on public transport vehicles (Smart Traffic Fund, Transport Department, HKSAR)

• 2021.7 -- 2024.10    PI, Edge-assisted Deep Learning Inference for Smart Internet-of-Things (Hong Kong Polytechnic University)

Honors (Since 2025)

1. 2026 Best Editor of IEEE Wireless Communications Letters

2. The World’s Top 2% Scientists for Career-Long Impact and Single-Year Impact (released by Stanford University and ELSEVIER in September 2025)

Professional Society Membership

• Senior Member, IEEE