Kezhi Wang

Professor Kezhi Wang is a Professor in the Department of Computer Science at Brunel University's College of Engineering, Design and Physical Sciences. He is a Royal Society Industry Fellow and a Highly Cited Researcher by Clarivate Web of Science (2023, 2024). With over 140 IEEE journal publications, 13,000+ citations, and an h-index of 55, his research has significant global impact.

His primary research interests lie in Machine Learning, Wireless Communications, and Edge Computing. These areas are pivotal for developing intelligent communication systems, next-generation wireless networks, and distributed AI at the edge. His contributions have yielded 5+ Clarivate ESI hot papers (top 0.1%) and 18+ highly cited papers (top 1%), demonstrating exceptional influence in the field.

Professor Wang has received numerous prestigious awards and recognitions:

• IEEE Communications Society Leonard G. Abraham Prize (2022)
• IEEE Communications Society Heinrich Hertz Award (2023)
• IEEE Communications Society Fred W. Ellersick Prize (2024)
• Highly Cited Researcher by Clarivate Web of Science (2023, 2024)
• Top 2% Scientist of the World (Elsevier, 2022-2024)
• Distinguished Visiting Fellowship, The Royal Academy of Engineering
• Distinguished Lecturer, IEEE Vehicular Technology Society (2025-2027)
• ScholarGPS Highly Ranked Scholar (Overall: #1,367; Computer Science: #128)

As a dedicated mentor, Professor Wang has co-supervised multiple PhD students to completion, with many now holding positions at top universities and industries globally. He also serves as an external supervisor for students at institutions including Newcastle University and Queen Mary University of London. His research group benefits from extensive international collaborations through EU Horizon Europe projects (HarmonicAI and COVER), enabling student secondments to leading institutions in Sweden, Germany, Netherlands, Canada, and Australia.

He leads a vibrant research team focused on cutting-edge projects in wireless communications and machine learning, with strong industry partnerships and active participation in major EU-funded initiatives. Current projects emphasize reconfigurable intelligent surfaces, UAV communications, and edge AI, positioning his group at the forefront of next-generation network research.