Homepage
Home
Teaching
Photograph
Useful Links
FL Seminar
NICE, SIST

Jingyang (William) Zhu 朱敬阳

alt text 

Hello everyone! I am currently a forth-year phd student advised by Prof. Yuanming Shi at School of Information Science and Technology (SIST), ShanghaiTech University, majoring in CS.

Earlier, I received my bachelor's degree in Electronic and Information Engineering from School of Electronic Engineering (SEE), Xidian University in 2021.

My research interest lies in the intersection of machine learning and communication networks, in particular federated learning, mathematical optimization as well as their applications to satellite communications and edge AI [Google Scholar].

Email: zhujy2@shanghaitech.edu.cn

Address: Rm. 2-309, SIST Building 2, 393 Middle Huaxia Road, Pudong New District, Shanghai 201210, China.

Research

My research interests include

  • Distributed Learning and Optimization.

  • 5G/6G, Wireless Communication, Signal Processing.

  • Routing in Satellite Networks, Graph-Based Algorithms.

Services

  • Reviewer of Journals

  1. IEEE Internet of Things Journal

  2. IEEE Transactions on Communications

  3. IEEE Transactions on Wireless Communications

  4. IEEE Open Journal of the Communications Society

Preprints

  1. Z. Wang, Y. Shi, Y. Zhou, J. Zhu, and K. B. Letaief, "Edge Large AI Models: Revolutionizing 6G Networks ", submitted to IEEE Communications Magazine for possible publication, Dec. 2024.

  2. Y. Shi, J. Zhu, C. Jiang, L. Kuang, and K. B. Letaief, "Satellite Edge Artificial Intelligence with Large Models: Architectures and Technologies ", submitted to Science China Information Sciences for possible publication, Major Revision, Jan. 2025.

  3. J. Zhu, Y. Shi, Y. Zhou, C. Jiang, and L. Kuang, "Hierarchical Learning and Computing over Space-Ground Integrated Networks ", submitted to IEEE Transactions on Mobile Computing for possible publication, Major Revision, Oct. 2024. [pdf]

  4. H. Yang, S. Xia, J. Zhu, Y. Wu, Y. Zhou, and Y. Shi, "Provable Guarantees for Over-the-Air Federated Learning with Polynomial Neural Networks ", submitted to IEEE Transactions on Wireless Communications for possible publication.

Publications

  • Journal Articles

  1. Y. Shi, L. Zeng, J. Zhu, Y. Zhou, C. Jiang, and K. B. Letaief, "Satellite Federated Edge Learning: Architecture Design and Convergence Analysis ", IEEE Trans. Wireless Commun., vol. 23, no. 10, Oct. 2024. [pdf]

  2. J. Zhu, Y. Shi, Y. Zhou, C. Jiang, W. Chen, and K. B. Letaief, "Over-the-Air Federated Learning and Optimization ", IEEE Internet Things J., vol. 10, no. 11, pp. 16996 - 17020, May 2024. [pdf]

  3. J. Zhu, Y. Shi, M. Fu, Y. Zhou, Y. Wu, and L. Fu, "Latency Minimization for Wireless Federated Learning with Heterogeneous Local Model Updates ", IEEE Internet Things J., vol. 11, no. 1, pp. 444-461, Jan. 2024. [pdf]

  • Conference Proceedings

  1. Z. Yang, P. Zhang, J. Zhu, D. Wen, Y. Shi, and W. Chen, "Hierarchical Federated Learning with Integrated Sensing-Communication-Computation over Space-Air-Ground Integrated Networks," in Proc. IEEE Int. Conf. Commun. (ICC), Montreal, Canada, Jun. 2025, ACCEPTED.

  2. R. Li, J. Zhu, Y. Mao, Y. Shi, T. Wang, C. Jiang, "Topology-Aware Routing for Federated Learning Over Multi-Layer Satellite Networks ", in Proc. IEEE Wireless Commun. Netw. Conf. (WCNC), Mar. 2025, Milan, Italy, ACCEPTED.

  3. Y. Zhu, P. Yang, J. Zhu, D. Wen, T. Wang, Y. Zhou, and C. Jiang, "Satellite Federated Fine-tuning for Foundation Models: Architecture Design and System Optimization ", in Proc. IEEE Global Conf. Commun. (GLOBECOM), Dec.2024, Cape Town, South Africa, ACCEPTED.

  4. Y. Wang, J. Zhu, Y. Mao, D. Wen, X. Tian, and Y. Shi, "Hierarchical Federated Edge Learning over Space-Air-Ground Integrated Networks ", in Proc. IEEE GLOBECOM WORKSHOPS (GC WKSHPS), Dec. 2023, Kuala Lumpur, Malaysia. [pdf]

  5. J. Zhu, Y. Shi, M. Fu, Y. Zhou, Y. Wu, and L. Fu, "Latency Minimization for Wireless Federated Learning with Heterogeneous Local Updates ", in Proc. IEEE Wireless Commun. Netw. Conf. (WCNC), Mar. 2023, Glasgow, Scotland. [pdf]

  6. S. Xia, J. Zhu, Y. Yang, Y. Zhou, Y. Shi, and W. Chen, "Fast Convergence Algorithm for Analog Federated Learning," in Proc. IEEE Int. Conf. Commun. (ICC), Online, 2021. [pdf]