Osvaldo Simeone is a Professor
of Information Engineering with the Centre for Telecommunications
Research at the Department of Engineering of King's College London,
where he directs the King's Communications, Learning and Information
Processing lab. He received
an M.Sc. degree (with honors) and a Ph.D. degree in information
engineering from Politecnico di Milano, Milan, Italy, in 2001 and 2005,
respectively. From 2006 to 2017, he was a faculty
member of the Electrical and Computer Engineering (ECE) Department at
New Jersey Institute of Technology (NJIT), where he was affiliated with
the Center for Wireless Information Processing (CWiP). His
research interests include information theory, machine learning,
wireless communications, neuromorphic computing, and quantum machine
learning. Dr Simeone is a co-recipient of the 2022 IEEE Communications Society Outstanding Paper Award, the 2021 IEEE Vehicular Technology Society Jack Neubauer Memorial Award, the 2019 IEEE Communication Society Best Tutorial Paper Award, the 2018 IEEE Signal Processing Best Paper Award, the
2017 JCN Best Paper Award, the 2015 IEEE Communication Society
Best Tutorial Paper Award and of the Best Paper Awards of
IEEE SPAWC 2007 and IEEE WRECOM 2007. He was awarded an Open Fellowship by the EPSRC in 2022 and a
Consolidator grant by the European Research Council (ERC) in 2016. His
research has been also supported by the U.S. National Science
Foundation, the European Commission, the European Research Council, the
Vienna Science and Technology Fund, the European Space Agency, as well
as by a number of industrial collaborations including with Intel Labs
and InterDigital. He is the Chair of the Signal Processing for
Communications and Networking Technical Committee of the IEEE Signal
Processing Society and of the UK & Ireland Chapter of the IEEE
Information Theory Society. He is currently a Distinguished Lecturer of
the IEEE Communications Society, and he was a Distinguished Lecturer of the IEEE Information Theory Society in 2017 and 2018.
Dr Simeone is the author of the textbook "Machine Learning for
Engineers" published by Cambridge University Press, four
monographs, two edited books, and more than 180 research journal and
magazine papers. He is a Fellow of the IET, EPSRC, and IEEE.