Dr. Zonghang Li

Email: lizhuestc@gmail.com    Wechat: lizh_uestc    Github: https://github.com/Lizonghang

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Hi! I am Zonghang Li, a Ph.D. graduate from the School of Information and Communication Engineering at University of Electronic Science and Technology of China (UESTC), advised by Prof. Hongfang Yu. Before that, I received my Bachelor’s degree (2018) from UESTC. I visited University of Oxford in 2018, Peng Cheng Laboratory in 2020 advised by Prof. Zenglin Xu, and Nanyang Technological University (NTU) in 2021 advised by Prof. Dusit Niyato and Prof. Han Yu. Now, I am doing postdoc research at MBZUAI with Prof. Mohsen Guizani.

My research interests are mainly in Distributed AI Systems, Algorithms, and Applications, including:

  • Optimizations for Large Model Training & Inference
  • Computer Network for Distributed ML Systems
  • Efficient and Robust Federated Learning

I am also interested in Reinforcement Learning, Diffusion Models, and other fantastic technologies.

Now, I have published more than 20 academic papers in top-tier journals including IEEE/ACM TON, IEEE TSC, IEEE TMC, IEEE JSAC, IEEE COMST, IEEE Wire. Comm., IEEE TCC, IEEE TNSM, IEEE Network, and IEEE IoT-J. I also contributed to a work presented on NSDI 2024. In addition, I obtained 6 CN Patents and authored one book titled “Geo-distributed Machine Learning: Enabling Integration of Intelligence on Multiple Clouds. My work GeoMX won the Future Network Leading Innovative Scientific and Technological Achievement Award of China Institute of Communications in 2021, and one paper won the Best Paper Award in Guangdong Computer Society in 2023. I serve as an assistant area editor in IEEE IoT-J, an assistant editor in IEEE COMST and IEEE Network, an assistant guest editor in IEEE VTM, IEEE IoTM, and a TPC member in HPCC 2021, WCNC 2022-2023, and iThings 2023. I also serve as a reviewer in IEEE TNNLS, IEEE TSC, IEEE TWC, IEEE TVT, IEEE TCCN, IEEE COMST, IEEE Network, IEEE VTM, IEEE IoT-J, J-STSP, and Cluster Computing.

news

Aug 05, 2024 Our paper titled “Energy-Efficient Hierarchical Collaborative Learning over LEO Satellite Constellations” is accepted by IEEE JSAC (CCF A)! :tada:
Jun 06, 2024 Our paper titled “Accelerating Geo-distributed Machine Learning with Network-Aware Adaptive Tree and Auxiliary Route” is accepted by IEEE/ACM TON (CCF A)! :tada:
Jun 05, 2024 I joined MBZUAI as a postdoc researcher, the first AI University in the world, with Prof. Mohsen Guizani! :tada::tada::tada:
May 01, 2024 I am selected as an Excellent PhD Graduates in UESTC! :tada:
Feb 28, 2024 Congratulations! Our geo-distributed machine learning system GeoMX is adopted and deployed at ZTE Co., Ltd.! :tada::tada::tada:

selected publications

  1. ACM TON (CCF A)
    Accelerating Geo-distributed Machine Learning with Network-Aware Adaptive Tree and Auxiliary Route
    Zonghang Li, Wenjiao Feng, Weibo Cai, and 5 more authors
    IEEE/ACM Transactions on Networking, 2024
  2. Book
    Geo-distributed Machine Learning: Enabling Integration of Intelligence on Multiple Clouds
    Hongfang Yu, Zonghang Li, Gang Sun, and 1 more author
    Publishing House of Electronics Industry. Student first author , 2023
  3. IEEE TSC (CCF A)
    ESync: Accelerating Intra-Domain Federated Learning in Heterogeneous Data Centers
    Zonghang Li, Huaman Zhou, Tianyao Zhou, and 3 more authors
    IEEE Transactions on Services Computing, 2022
  4. IEEE Network (Q1)
    Byzantine Resistant Secure Blockchained Federated Learning at the Edge
    Zonghang Li, Hongfang Yu, Tianyao Zhou, and 4 more authors
    IEEE Network, 2021
  5. IEEE IoTJ (Q1)
    Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
    Zonghang Li, Yihong He, Hongfang Yu, and 4 more authors
    IEEE Internet of Things Journal, 2022
  6. IEEE TMC (CCF A)
    Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services
    Hongyang Du, Zonghang Li, Dusit Niyato, and 4 more authors
    IEEE Transactions on Mobile Computing. Co-first author , 2024
  7. IEEE TSC (CCF A)
    NBSync: Parallelism of Local Computing and Global Synchronization for Fast Distributed Machine Learning in WANs
    Huaman Zhou, Zonghang Li, Hongfang Yu, and 2 more authors
    IEEE Transactions on Services Computing, 2023
  8. IEEE JSAC (CCF A)
    Personalized Saliency in Task-Oriented Semantic Communications: Image Transmission and Performance Analysis
    Jiawen Kang, Hongyang Du, Zonghang Li, and 4 more authors
    IEEE Journal on Selected Areas in Communications. Best Paper Award , 2023
  9. IEEE Wire. Comm. (Q1)
    Enabling AI-Generated Content Services in Wireless Edge Networks
    Hongyang Du, Zonghang Li, Dusit Niyato, and 4 more authors
    IEEE Wireless Communications. Co-first author , 2024
  10. IEEE JSAC (CCF A)
    Energy-Efficient Hierarchical Collaborative Learning over LEO Satellite Constellations
    Long Luo, Chi Zhang, Hongfang Yu, and 3 more authors
    IEEE Journal on Selected Areas in Communications, 2024
  11. IEEE COMST (Q1)
    Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization
    Hongyang Du, Ruichen Zhang, Yinqiu Liu, and 8 more authors
    IEEE Communications Surveys & Tutorials. Co-first author , 2023
  12. IEEE TCC (Q1)
    HFedMS: Heterogeneous Federated Learning With Memorable Data Semantics in Industrial Metaverse
    Shenglai Zeng, Zonghang Li, Hongfang Yu, and 4 more authors
    IEEE Transactions on Cloud Computing. Co-first author , 2023
  13. DASFAA
    Heterogeneous Federated Learning via Grouped Sequential-to-parallel Training
    Shenglai Zeng, Zonghang Li, Hongfang Yu, and 4 more authors
    In DASFAA . Co-first author , 2022
  14. IEEE TNSM (Q1)
    TSEngine: Enable Efficient Communication Overlay in Distributed Machine Learning in WANs
    Huaman Zhou, Weibo Cai, Zonghang Li, and 4 more authors
    IEEE Transactions on Network and Service Management, 2021
  15. FGCS (Q1)
    DGT: A Contribution-aware Differential Gradient Transmission Mechanism for Distributed Machine Learning
    Huaman Zhou, Zonghang Li, Qingqing Cai, and 4 more authors
    Future Generation Computer Systems, 2021