Liu Zhenyu

Dr. Zhenyu Liu joined Tsinghua Shenzhen International Graduate School as an Assistant Professor in September 2023. He was a Postdoctoral Associate at the Laboratory for Information and Decision Systems at the Massachusetts Institute of Technology (MIT) from 2022 to 2023. Dr. Liu received the Ph.D. degree in networks and statistics from MIT. He received the B.S. degree (with honor) and the M.S. degree in electronic engineering from Tsinghua University, Beijing, China. His research interests include wireless communication, signal processing, statistical inference, networked control, network localization and navigation, and Internet-of-Things. He has been a regular reviewer for multiple IEEE journals.

09/2014-05/2022, Massachusetts Institute of Technology, Networks and Statistics, Ph.D.

09/2011-05/2014, Tsinghua University, Information and Communication Engineering, Master

08/2007-07/2011, Tsinghua University, Electronic Information Science and Technology, Bachelor

09/2023-Present, Tsinghua University Shenzhen International Graduate School, Assistant Professor

07/2022-06/2023, Massachusetts Institute of Technology, Postdoctoral Associate

Research Interest

-Decentralized inference and learning

-Network localization and navigation

-Next generation wireless communication

-Sensor networks and Internet-of-Things

[1] Z. Liu, A. Conti, S. K. Mitter, and M. Z. Win, “Communication-Efficient Distributed Learning over Networks–Part I: Sufficient Conditions for Accuracy,” IEEE J. Sel. Areas Commun., vol. 41, no. 4, pp. 1081–1101, Apr. 2023.

[2] Z. Liu, A. Conti, S. K. Mitter, and M. Z. Win, “Communication-Efficient Distributed Learning over Networks–Part II: Necessary Conditions for Accuracy,” IEEE J. Sel. Areas Commun., vol. 41, no. 4, pp. 1102–1119, Apr. 2023.

[3] Z. Liu, A. Conti, S. K. Mitter, and M. Z. Win, “Continuous-Time Distributed Filtering with Sensing and Communication Constraints,” IEEE J. Sel. Areas Inf. Theory, 2023, to appear.

[4] Z. Liu, A. Conti, S. K. Mitter, and M. Z. Win, “Filtering over Non-Gaussian Channels: The Role of Anytime Capacity,” IEEE Contr. Syst. Lett., vol. 7, pp. 472–477, 2023.

[5] Z. Liu, W. Dai, and M. Z. Win, “Mercury: An Infrastructure-Free System for Network Localization and Navigation,” IEEE Trans. Mobile Comput., vol. 17, no. 5, pp. 1119–1133, May 2018.