Imperial College London


Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor in Information Processing



+44 (0)20 7594 6218d.gunduz Website




Ms Joan O'Brien +44 (0)20 7594 6316




1016Electrical EngineeringSouth Kensington Campus





Deniz Gündüz received the B.S. degree in electrical and electronics engineering from METU, Ankara, Turkey, in 2002, and the M.S. and Ph.D. degrees in electrical engineering from NYU Polytechnic School of Engineering (formerly Polytechnic University), Brooklyn, NY, in 2004 and 2007, respectively. He is currently a Professor in Information Processing in the Electrical and Electronic Engineering Department of Imperial College London, and is leading the Information Processing and Communications Lab. He is also the Deputy Head of the Intelligent Systems and Networks Group. He had part-time / visiting faculty positions at the "Enzo Ferrari" Department of Engineering at the University of Modena and Reggio Emilia (2019-2022), University of Padova (2018-2020) and Princeton University (2009-2012). Previously he was a Research Associate at CTTC, Barcelona, Spain, a Consulting Assistant Professor at the Department of Electrical Engineering, Stanford University, and a postdoctoral Research Associate at the Department of Electrical Engineering, Princeton University. 

Dr. Gündüz is an Area Editor for the IEEE Transactions on Information Theory (2021-) for Signal Processing and Source Coding Area, an Area Editor for IEEE Transactions on Communications (2020 - ) for the "machine learning and communications" area, and an Editor of the IEEE Transactions on Wireless Communications (2019 - ). Previously he served as an Area Editor for the IEEE Journal on Selected Areas in Communications (JSAC), Special Series on Machine Learning in Communications and Networks, Distributed/Federated Learning and Communications Area (2020-2022), and as an Editor for the IEEE Transactions on Communications (2013 - 2018), the IEEE Transactions on Green Communications and Networking (2016 - 2020), the IEEE Journal on Selected Areas in Communications (JSAC), Series on Green Communications and Networking (2015 - 2016), and as a Guest Editor for various special issues for the IEEE Journal on Selected Areas in Communications (JSAC), IEEE Journal on Selected Areas in Information Theory (JSAIT), Journal of The Franklin Institute, IEEE Transactions on Green Communications and Networking, and for the EURASIP Journal on Wireless Communications and Networking. He was a Distinguished Lecturer of the IEEE Information Theory Society (2020 - 2022). He has been active in the regeneration of the London Symposium on Information Theory, and has served as its co-chair since 2019.

Dr. Gündüz is the recipient of the 2017 Early Achievement Award of the IEEE Communication Society - Communication Theory Technical Committee (CTTC), Starting (2015), Consolidator (2022) and Proof-of-Concept (2023) grants of the European Research Council (ERC), the 2014 IEEE Communication Society Best Young Researcher Award for the Europe, Middle East and Africa Region, and the 2008 Alexander Hessel Award awarded by the Electrical and Computer Engineering Department of New York University Polytechnic School of Engineering for the best Ph.D. dissertation. He is a co-author of the paper that received the IEEE Communications Society - Young Author Best Paper Award in 2022, as well as the papers that received the Best Paper Awards at the 2016 IEEE Wireless Communications and Networking Conference (WCNC), and 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), and the Best Student Paper Award at the 2018 IEEE WCNC and 2007 International Symposium on Information Theory (ISIT).

His research interests lie in the areas of communication theory, information theory, machine learning and privacy.

You can follow his publications and citations on the Google Scholar page.

A more frequently updated website of his research group can be found here.



Song J, Gunduz D, Choi W, 2024, Optimal Scheduling Policy for Minimizing Age of Information With a Relay, Ieee Internet of Things Journal, Vol:11, Pages:5623-5637

Hu Z, Liu G, Xie Q, et al., 2024, A learnable optimization and regularization approach to massive MIMO CSI feedback, Ieee Transactions on Wireless Communications, Vol:23, ISSN:1536-1276, Pages:104-116

Ozfatura K, Ozfatura E, Kupcu A, et al., 2024, Byzantines Can Also Learn From History: Fall of Centered Clipping in Federated Learning, Ieee Transactions on Information Forensics and Security, Vol:19, ISSN:1556-6013, Pages:2010-2022

Wang Y, Gao Z, Zheng D, et al., 2023, Transformer-Empowered 6G Intelligent Networks: From Massive MIMO Processing to Semantic Communication, Ieee Wireless Communications, Vol:30, ISSN:1536-1284, Pages:127-135

Zheng J, Ni W, Tian H, et al., 2023, Semi-federated learning: convergence analysis and optimization of a hybrid learning framework, Ieee Transactions on Wireless Communications, Vol:22, ISSN:1536-1276, Pages:9438-9456

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