Mehdi Bennis (University of Oulu, Finland)
Mehdi Bennis is an associate professor at the University of Oulu, Finland. He received his M.Sc. degree from the cole Polytechnique Federale de Lausanne (EPFL), Switzerland and the Eurecom Institute, France in 2002. He obtained his Ph.D. degree in electrical engineering December 2009 on spectrum sharing for future mobile cellular systems. His main research interests are in radio resource management, heterogeneous networks, game theory and machine learning. He has published more than 100 research papers in international conferences, journals, book chapters and patents. Dr Bennis gave a dozen of tutorials at IEEE flagship conferences. He was also the recipient of several prizes including the 2015 Fred W. Ellersick Prize from the IEEE Communications Society (COMSOC), the 2016 IEEE COMSOC Best Tutorial Prize, the 2017 EURASIP Best Paper Award for the Journal on Wireless Communications and Networking (JWCN), and recently the best paper Award at EUCNC 2017.
Title: “Wireless Edge intelligence: Vision, Algorithms and Applications”
Short abstract: In just a few years, breakthroughs in machine learning (ML) and particularly deep learning have transformed every aspects of our lives from face recognition, medical diagnosis, and natural language processing. This progress has been fueled mainly by the availability of more data and more computing power. However, the current premise in classical ML is based on a single node in a centralized and remote data center with full access to a global dataset and a massive amount of storage and computing, sifting through this data for inference. Nevertheless the advent of a new breed of intelligent devices and high-stake applications ranging from drones to augmented/virtual reality applications and self-driving vehicles, makes cloud-based ML inadequate. This talk will present the vision of distributed edge intelligence for resource-constrained devices accompanied featuring key enablers, architectures, algorithms and some recent results.