Rate My Professor Kezhi Wang

Professor Kezhi Wang serves as Professor and Royal Society Industry Fellow in the Department of Computer Science within the College of Engineering, Design and Physical Sciences at Brunel University London. He earned his PhD in Engineering from the University of Warwick, supported by the Chancellor’s International Scholarship. Previously, he held positions at the University of Essex and Northumbria University. His research interests focus on machine learning, wireless communications, and edge computing, with key contributions in reconfigurable intelligent surfaces (RIS), UAV communications, and AI applications for digital health. Wang has led major funded projects, including the HarmonicAI initiative—Human-guided collaborative multi-objective design of explainable, fair and privacy-preserving AI for digital health—funded by the European Commission and UK Research and Innovation from February 2024 to January 2028. Additional grants include the NVIDIA Academic Grant Program Award, JSPS Invitational Fellowship, Horizon Europe MSCA Doctoral Networks ANT, Horizon Europe MSCA Postdoctoral Fellowship S-ISAC, and Royal Society International exchange projects.

Wang has garnered prestigious recognitions, such as Highly Cited Researcher by Clarivate Web of Science for 2023, 2024, and 2025; Top 2% Scientist of the World; Rising Star of Science Award from Research.com in 2025; and IEEE Communications Society awards including the Leonard G. Abraham Prize, Heinrich Hertz Award, and Fred W. Ellersick Prize. He holds the Distinguished Visiting Fellowship from the Royal Academy of Engineering and serves as Distinguished Lecturer for the IEEE Vehicular Technology Society from 2025 to 2027. With over 150 publications in IEEE journals, he boasts more than 16,000 citations and an h-index of 60 on Google Scholar. Notable works include 'Performance Analysis for RIS-Assisted SWIPT-Enabled IoT Systems' (IEEE Transactions on Wireless Communications, 2024), 'Two-Timescale Design for Reconfigurable Intelligent Surface-Aided Massive MIMO Systems with Imperfect CSI' (IEEE Transactions on Information Theory, 2022), 'Reconfigurable Intelligent Surfaces for 6G Systems: Principles, Applications, and Research Directions' (IEEE Communications Magazine, 2021), and 'Deep Reinforcement Learning Based Dynamic Trajectory Control for UAV-Assisted Mobile Edge Computing' (IEEE Transactions on Mobile Computing, 2021). Professionally, he edits for IEEE Transactions on Vehicular Technology and IEEE Wireless Communications Letters, holds IEEE Senior Membership, and serves on the UKRI Talent Peer Review College and as EPSRC Associate College Member. Wang has supervised multiple PhD students to completion and acted as external examiner and PhD examiner for numerous institutions worldwide.