IEEE Distinguished Lecturer Tour – Prof. Carlo Fischione
Date: July 23, 2026, 11:00 AM.
Venue: Seminar Room, Alan Turing, University of L’Aquila
Title: AI in Wireless Networks: What Works, What Doesn’t, and What Comes Next
Abstract: Artificial Intelligence and Machine Learning are widely seen as key enablers of future wireless systems, with promises ranging from fully autonomous networks to dramatic gains in spectral efficiency and energy consumption. However, many of these expectations are based on implicit assumptions, such as abundant data, reliable connectivity, and centralized computation, that do not hold in practical radio environments.
In this talk, we critically examine the myths and realities of AI/ML in wireless networks, with a focus on what can be realistically achieved within the constraints of modern radio systems. We discuss why the straightforward application of data-driven methods often falls short in distributed, bandwidth-limited, and latency-constrained settings, and highlight common pitfalls in current approaches to learning over wireless infrastructures.
Building on this analysis, we motivate the co-design of communication and computation, where the wireless channel is not just a medium for data transfer, but an active component of distributed learning and inference. Leveraging recent advances in over-the-air computation and its digital implementations (e.g., ChannelComp), we outline how AI-native radio systems can emerge by embedding learning objectives directly into the physical layer.
Bio: Dr. Carlo Fischione is full Professor at KTH Royal Institute of Technology, Electrical Engineering and Computer Science, Division of Network and Systems Engineering (NSE), Stockholm, Sweden. Prof. Fischione is Fellow of IEEE (the Institute of Electrical and Electronic Engineers), AAIA (Asian-Pacific Artificial Intelligence Association), DF (KTH Digital Futures research center), and DASP (the Italian academy of history Deputazione Abruzzese di Storia Patria) and is Distinguished Lecturer of the IEEE Communication Society. He is Director of the undergraduate education at NSE Department of KTH, Chair of the IEEE Machine Learning for Communications Emerging Technologies Initiative, founding General Chair and Steering Commitee Chair of the IEEE International Conference on Machine Learning for Communications and Networking – IEEE ICMLCN, and was the founding Director of the KTH-Ericsson Data Science Micro Degree Program directed to Ericsson globally. Prof. Fischione is the IEEE ComSoc delegate to the IEEE AI Alliance. He received the Ph.D. degree in Electrical and Information Engineering (3/3 years) in May 2005 and the Laurea degree in Electronic Engineering (Laurea, Summa cum Laude, 5/5 years) in April 2001, both from University of L’Aquila, Italy. He received the Starting Grant of the Swedish Research Council in 2008. Prof. Fischione has held research positions at Massachusetts Institute of Technology, Cambridge, MA (2015, Visiting Professor); Harvard University, Cambridge, MA (2015, Associate); and University of California at Berkeley, CA (2004-2005, Visiting Scholar, and 2007-2008, Research Associate). He is Professor on the Doctoral School of University of L’Aquila, Italy, Department of Mathematics, Information Engineering, and Computer Science. His research interests include applied optimization, wireless Internet of Things, and machine learning. He received a number of awards, such as the “IEEE Communication Society S. O. Rice” award for the best IEEE Transactions on Communications paper of 2018, the best paper award of IEEE Transactions on Industrial Informatics (2007). He is Editor of IEEE Transactions on Communications (Machine Learning for Communications area) and IEEE Transactions on Machine Learning for Communication and Networking, and has served as Associated Editor of IFAC Automatica (2014-2019). He is co-founder of the company ELK.Audio.
