KEYNOTE SPEAKER

Into The Wireless Metaverse: A Rendez-Vous Between 6G Systems and Artificial Intelligence (AI)

PROF. WALID SAAD

 

Abstract: The metaverse is set to revolutionize the way people interact, communicate, and conduct business, blurring the lines between virtual, digital, and physical worlds. This transformation is critical for the advancement of tomorrow's Society 5.0, where a harmonious integration of cyber and physical spaces can address emerging social challenges while boosting economic progress. However, deploying the metaverse at scale to enable global interactivity requires a confluence of cutting-edge technologies, from wireless communication systems to digital twins, extended reality, and artificial intelligence (AI). In this talk, we explore new frameworks for the synergistic integration of these technologies, and explore how this integration has the potential to catalyze the deployment of a limitless, wireless metaverse. We start by investigating whether key capabilities of 6G systems, such as terahertz communications and mobile edge computing, can deliver the physical experience and synchronization necessary to create a seamless connection between the virtual and physical worlds. We then examine the advancements required in the field of AI to achieve cognition and reasoning in wireless networks. In this space, we first discuss the role of continual learning in synchronizing digital twins in the metaverse. Then, we introduce a holistic vision for semantic communications that is firmly grounded in rigorous AI foundations, with the potential to revolutionize the way information is modeled, transmitted, and processed in communication systems We show how, by embracing semantic communication through our proposed vision, we can usher in a new era of knowledge-driven, reasoning wireless networks that are more sustainable and resilient than today's data-driven, knowledge-agnostic networks. As a first step towards enabling this paradigm shift, we present our recent key results in this area that showcase how the use of semantic communications can reduce the volume of data circulating in a network while improving reliability, two critical requirements for the metaverse and its applications. We conclude by articulating a research roadmap that delineates the requisite innovations at the confluence of AI, 6G, and computing to fully realize the potential of the wireless metaverse.

 

Biography:  Walid Saad (S’07, M’10, SM’15, F’19) received his Ph.D degree from the University of Oslo, Norway in 2010. He is currently a Professor at Virginia Tech's Electrical and Computer Engineering Department where he leads the Network sciEnce, Wireless, and Security (NEWS) group. He is also the Next-G Wireless Faculty Lead at Virginia Tech's Innovation Campus. His research interests include wireless networks (5G/6G/beyond), machine learning, game theory, security, UAVs, semantic communications, cyber-physical systems, and network science. Dr. Saad is a Fellow of the IEEE. He is also the recipient of the NSF CAREER award in 2013 and the Young Investigator Award from the Office of Naval Research (ONR) in 2015. He was the (co-)author of eleven conference best paper awards at IEEE WiOpt in 2009, ICIMP in 2010, IEEE WCNC in 2012, IEEE PIMRC in 2015, IEEE SmartGridComm in 2015, EuCNC in 2017, IEEE GLOBECOM (2018 and 2020), IFIP NTMS in 2019, IEEE ICC (2020 and 2022). His research was recognized with the prestigious IEEE Fred W. Ellersick Prize from the IEEE Communications Society (ComSoc) in 2015 and 2022. He was also a co-author of the papers that received the 2019 and 2021 IEEE Communications Society Young Author Best Paper award. Other recognitions include the 2017 IEEE ComSoc Best Young Professional in Academia award, the 2018 IEEE ComSoc Radio Communications Committee Early Achievement Award, and the 2019 IEEE ComSoc Communication Theory Technical Committee Early Achievement Award. He has been annually listed in the Clarivate Web of Science Highly Cited Researcher List since 2019. Dr. Saad is currently the Editor-in-Chief for the IEEE Transactions on Machine Learning in  Communications and Networking.