Abstract: As data generation increasingly takes place on devices without a wired connection, the data traffic generated by intelligent services (IS), such as Machine Learning ML or Artificial Intelligence, will be ubiquitous in wireless networks. Many studies have shown that traditional wireless protocols are highly inefficient or unsustainable to support IS in terms of reliability, energy, bandwidth, delay, privacy and security. These challenges create the need for fundamentally new wireless communication methods specifically intended for IS. In this talk, first we review the state-of-the-art, namely analog over-the-air wireless protocols. Then we show that retransmission protocols for analog over-the-air may have an essential role to increase reliability. However, the widespread use of digital modulations may hinder such computation protocols. Thus, we will introduce the fundamentally new method of digital over-the-air computation, which uses any digital modulations as opposed to amplitude analog modulations of the traditional over-the-air computation protocols. This talk gives an introduction to these methods, reviews the most important works, highlights open problems, and discusses application scenarios.
Bio: Dr. Carlo Fischione is full Professor at KTH Royal Institute of Technology, Electrical Engineering and Computer Science, Division of Network and Systems Engineering, Stockholm, Sweden. He is Director of the KTH-Ericsson Data Science Micro Degree Program directed to Ericsson globally, and Chair of the IEEE Machine Learning for Communications Emerging Technologies Initiative. He is distinguished lecturer of the IEEE Communication Society, and the funding Chair of the first IEEE International Conference on Machine Learning for Communication and Networking (IEEE ICMLCN 2024). 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 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 Honorary Professor at University of L’Aquila, Italy, Department of Mathematics, Information Engineering, and Computer Science.
His research interests include applied optimization, wireless, sensor networks, Internet of things, and machine learning. He has co-authored over 200 publications, including a book, book chapters, international journals and conferences, and international patents. 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 Journal on Selected Areas on Communications (Series on Machine Learning for Communication and Networking), and has been serving as Associated Editor of IFAC Automatica (2014-2019). He is co-founder and scientific advisor of ELK.Audio. He is Member of IEEE (the Institute of Electrical and Electronic Engineers), and Ordinary Member of DASP (the Italian academy of history Deputazione Abruzzese di Storia Patria).
When: Thurdsay, July 13, at 10:30 – 11:15 AM
Where: Seminar room of Alan Turing building (Coppito 0)