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Shi Yuanming
Professor
Graduated School: The Hong Kong University of Science and Technology
Tel: 021-20685374
Office: 2-302F
Homepage: https://faculty.sist.shanghaitech.edu.cn/faculty/shiym/home.html
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Research Area: edge AI, space computing, wireless communications, and large-scale optimization
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Dr. Yuanming Shi received the B.S. degree in electronic engineering from Tsinghua University, Beijing, China, in 2011. He received the Ph.D. degree in electronic and computer engineering from The Hong Kong University of Science and Technology (HKUST), in 2015. Since September 2015, he has been with the School of Information Science and Technology in ShanghaiTech University, where he is a Full Professor. He visited University of California, Berkeley, CA, USA, from October 2016 to February 2017. His research areas include edge AI, space computing, wireless communications, and large-scale optimization. He is a recipient of the IEEE Marconi Prize Paper Award in Wireless Communications in 2016, the Young Author Best Paper Award by the IEEE Signal Processing Society in 2016, the IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2021, and the Chinese Institute of Electronics First Prize in Natural Science in 2022, and the Best Paper Award from IEEE International Mediterranean Conference on Communications and Networking (MeditCom) in 2023. He is also an editor of IEEE Transactions on Wireless Communications, IEEE Journal on Selected Areas in Communications, and Journal of Communications and Information Networks. He is an IET Fellow.

  • Space Computing Networks 

  1.  Y. Shi, L. Zeng, J. Zhu, Y. Zhou, C. Jiang, K. B. Letaief, “Satellite Federated Edge Learning: Architecture Design and Convergence Analysis”, IEEE Trans. Wireless Commun., 2024.

 

  • Edge AI

  1. K. B. Letaief, Y. Shi, J. Lu, and J. Lu, “Edge artificial intelligence for 6G: vision, enabling technologies, and applications,” IEEE J. Select. Areas Commun., vol. 40, no. 1, pp. 5 - 36, Jan. 2022.

  2. K. Yang, T. Jiang, Y. Shi, and Z. Ding, “Federated learning via over-the-air computation,” IEEE Trans. Wireless Commun., vol. 19, no. 3, pp. 2022-2035, Mar. 2020.

 

  • Wireless Communications 

  1. K. B. Letaief, W. Chen, Y. Shi, J. Zhang, and Y. Zhang, “The roadmap to 6G - AI empowered wireless networks,” IEEE Commun. Mag., vol. 57, no. 8, pp. 84-90, Aug. 2019.

  2. S. Xie, S. Ma, M. Ding, M. Tang, Y. Shi, and Y. Wu, “Robust information bottleneck for task-oriented communication with digital modulation,” IEEE J. Select. Areas Commun., vol. 41, no. 8, pp. 2577 - 2591, Aug. 2023.

 

  • Large-Scale Optimization

  1. Y. Shi, L. Lian, Y. Shi, Z. Wang, Y. Zhou, L. Fu, L. Bai, J. Zhang, and W. Zhang, “Machine learning for large-scale optimization in 6G wireless networks,” IEEE Commun. Surveys Tuts., vol. 25, no.4, Fourth Quarter, 2023.

  2. 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.

  3. 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.