Deniz Gündüz is a Professor of Information Processing at Imperial College London's Electrical and Electronic Engineering Department, leading the Information Processing and Communications Lab. He also serves as Deputy Head of the Intelligent Systems and Networks Group and holds a part-time faculty position at the University of Modena and Reggio Emilia. His research focuses on wireless communications, information theory, machine learning, and privacy, with significant contributions to semantic communication systems and AI-native networks. He has held visiting roles at Princeton University and the University of Padova. Dr. Gündüz is an Area Editor for IEEE Transactions on Communications and IEEE JSAC, and a former Distinguished Lecturer of the IEEE Information Theory Society. His awards include the IEEE Communication Society Early Achievement Award (2017), ERC Starting Grant (2015), and multiple best paper recognitions. He has organized major conferences and workshops, including the first MLCOM workshops on machine learning for communications. Education: B.S. (2002) from METU, Turkey; M.S. and Ph.D. (2004, 2007) from NYU Polytechnic School of Engineering. Prior roles include Research Associate at CTTC Barcelona, Consulting Assistant Professor at Stanford, and postdoctoral positions at Princeton. His work spans theoretical foundations and practical implementations, emphasizing interdisciplinary solutions for next-generation networks. Research Interests: Semantic communications, distributed learning, 6G systems, privacy-preserving techniques, and AI integration in communication networks. His recent work explores neural compression for cloud RAN, over-the-air computation, and federated learning optimizations. Awards and Roles: IEEE JSAC Series Editor (Machine Learning in Networks), IEEE Transactions on Wireless Communications Editor, and organizer of major conferences. His team's achievements include breakthroughs in joint source-channel coding and adversarial jamming defenses.
