Jun Zhang

PhD, FIEEE
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Associate Professor, IEEE Fellow
Department of Electronic and Computer Engineering (ECE)
Computer Engineering Program (CPEG)
The Hong Kong University of Science and Technology (HKUST)

Office: Room 2430
Email: eejzhang@ust.hk
Phone: +852 2358-7050
[Google Scholar] [CV]

Opening

  • I am recruiting PhD students (Fall 2023) and postdocs/RAs (any time) on the following topics. Feel free to contact me if interested. [Opening]

    • Edge AI (task-oriented communications, deep video compression, and cooperative perception)

    • Cooperative AI (federated learning, multi-agent reinforcement learning)

    • Deep learning for wireless communications (with a focus on safety and robustness)

What's new

  • (Call for Paper) I am co-editing a special issue on 6G for The Information Theory Magazine (together with Jeffrey Andrews, Giuseppe Caire, Muriel Medard, Tom Richardson, Harish Vishwanathan). [Call for Paper]

  • (New Talk) “Task-oriented Communication for Edge AI”, Huawei – IEEE ITSoc HK Joint Workshop on Semantic Information Theory 2022. [Slides] [Video]

  • (New Paper) “Federated learning with GAN-based data synthesis for non-IID clients,” FL-IJCAI’22. [Paper]

  • (New Paper) “Graph neural networks for wireless communications: From theory to practice,” submitted. [Paper] [GitHub]

  • (New Paper) “Task-oriented communication for multi-device cooperative edge inference,” IEEE Trans. Wireless Commun., to appear. [Paper]

  • (New Paper) “Learning task-oriented communication for edge inference: An information bottleneck approach,” IEEE J. Select. Areas Commun, Jan. 2022. [Paper] [GitHub]

Research Interests

  • Edge AI and Edge Computing

    • Edge video analytics; deep image/video compression; cooperative perception

  • Cooperative AI

    • Privacy-preserving collaborative learning; multi-agent reinforcement learning

  • Wireless Communications and Networking

    • Machine-type communications (URLLC, Massive connectivity); machine learning for wireless communications

Selected Publications

  • Edge AI and Edge Computing

    • J. Shao, Y. Mao, and J. Zhang, “Task-oriented communication for multi-device cooperative edge inference,” IEEE Trans. Wireless Commun., to appear. [Paper]

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

    • J. Shao, J. Zhang, “Communication-computation trade-off in resource-constrained edge inference,” IEEE Commun. Mag., vol. 58, no. 12, pp. 20–26, Dec. 2020. [Paper] [GitHub]

  • Cooperative AI

    • Z. Li, J. Shao, Y. Mao, J. Wang, and J. Zhang, “Federated learning with GAN-based data synthesis for non-IID clients,” FL-IJCAI’22. [Paper]

    • Y. Sun*, J. Shao*, S. Li, Y. Mao, and J. Zhang, “Stochastic coded federated learning with convergence and privacy guarantees,” IEEE Int. Symp. Information Theory (ISIT), Espoo, Finland, June-July 2022. [Paper] (* equal contribution)

    • L. Liu, J. Zhang, S.H. Song, and K. B. Letaief, “Communication-efficient federated distillation with active data sampling,” IEEE Int. Conf. Commun. (ICC), Seoul, South Korea, May 2022. [Paper]

    • L. Liu, J. Zhang, S.H. Song, and K. B. Letaief, “Hierarchical quantized federated learning: Convergence analysis and system design,” IEEE Trans. Wireless Commun., to appear. [Paper]

  • Wireless Communications

    • Y. Shen, J. Zhang, S.H. Song, and K. B. Letaief, “Graph neural networks for wireless communications: From theory to practice,” submitted. [Paper] [GitHub]

    • Y. Shen, Y. Shi, J. Zhang, and K. B. Letaief, “Graph neural networks for scalable radio resource management: architecture design and theoretical analysis,” IEEE J. Select. Areas Commun, vol. 39, no. 1, pp. 101–115, Jan. 2021. [Paper]

    • X. Yu, J.-C. Shen, J. Zhang, and K. B. Letaief, “Alternating minimization algorithms for hybrid precoding in millimeter wave MIMO systems,” IEEE J. Sel. Topics Signal Process., vol. 10, no. 3, pp. 485-500, Apr. 2016. [Paper] [Codes] (The 2018 IEEE Signal Processing Society Young Author Best Paper Award)

    • Y. Shi, J. Zhang, and K. B. Letaief, “Group sparse beamforming for green Cloud-RAN,” IEEE Trans. Wireless Commun., vol. 13, no. 5, pp. 2809-2823, May 2014. [Paper] [Codes] (The 2016 Marconi Prize Paper Award)