AI at the Wireless Edge: From Distributed Learning to Over-the-Air Model Aggregation
Prof. Carlo Fischione
Kungliga Tekniska Högskolan, Sweden
Abstract: Artificial Intelligence is transforming wireless communication systems, introducing new design principles rooted in learning, adaptation, and collaboration. This seminar offers a research-oriented overview of how AI is being integrated into the wireless edge, focusing on distributed learning frameworks such as federated learning. We will discuss key challenges including communication efficiency, privacy preservation, and model heterogeneity—especially under the stringent constraints of latency and bandwidth. A particular emphasis will be placed on Digital Over-the-Air Computation, an emerging physical-layer technique that enables fast and scalable model aggregation by exploiting the wireless medium itself. The talk will highlight the interplay between AI, wireless system design, and optimization theory, aiming to shed light on the opportunities and open questions that define this rapidly evolving field.
Brief Biography of the Speaker: 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, 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 funding 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.