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 is also a part-time faculty member in the "Enzo Ferrari" Department of Engineering at the University of Modena and Reggio Emilia. He has held visiting positions at 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 the Area Editor for IEEE Transactions on Communications (2020 - ) for the "machine learning and communications" area, an Editor of the IEEE Transactions on Wireless Communications (2019 - ). Previously he served as an Editor for the IEEE Transactions on Communications (2013 - 2018), IEEE Transactions on Green Communications and Networking (2016 - 2020), IEEE Journal on Selected Areas in Communications (JSAC), Series on Green Communications and Networking (2015 - 2016), and as a Guest Editor for the IEEE JSAC Special Issue on Machine Learning in Wireless Communication Networks (2019), and for the EURASIP Journal on Wireless Communications and Networking, Special Issue on Recent Advances in Optimization Techniques in Wireless Communication Networks (2012). He is a Distinguished Lecturer of the IEEE Information Theory Society (2020 - 2022). He organised the first two workshops on "machine learning for communications" (MLCOM) in conjunction with IEEE International Conference on Communications (ICC) in 2018 and 2019. He was also a General Co-chair of the 2019 London Symposium on Information Theory, the 22nd International ITG Workshop on Smart Antennas, and 2016 IEEE Information Theory Workshop.
Dr. Gündüz is the recipient of the 2017 Early Achievement Award of the IEEE Communication Society - Communication Theory Technical Committee (CTTC), a Starting Grant of the European Research Council (ERC) in 2015, 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 also a recipient of 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.
Ceran E, Gunduz D, Gyorgy A, 2021, A reinforcement learning approach to age of information in multi-user networks with HARQ, Ieee Journal on Selected Areas in Communications, Vol:39, ISSN:0733-8716, Pages:1412-1426
Mashhadi MB, Yang Q, Gunduz D, 2021, Distributed deep convolutional compression for massive MIMO CSI feedback, Ieee Transactions on Wireless Communications, Vol:20, ISSN:1536-1276, Pages:2621-2633
Rassouli B, Gunduz D, 2021, On perfect privacy, Ieee Journal on Selected Areas in Information Theory, Vol:2, ISSN:2641-8770, Pages:177-191
Jankowski M, Gunduz D, Mikolajczyk K, 2021, Wireless image retrieval at the edge, Ieee Journal on Selected Areas in Communications, Vol:39, ISSN:0733-8716, Pages:89-100
et al., 2021, Series editorial: inauguration issue of the series on machine learning in communications and networks, Ieee Journal on Selected Areas in Communications, Vol:39, ISSN:0733-8716, Pages:1-3