IEEE Talk: Building Foundation Models and Generalizable AI in 6G

#telecom #communications #6G #AI

Speaker: Dr. Hatem Abou-Zeid, Assistant Professor
Department of Electrical and Software Engineering, University of Calgary

Abstract: Artificial intelligence capabilities are envisioned to transform the design and operation of 6G networks. While research efforts have demonstrated the potential of AI for wireless, the lack of generalization and the need for tailored AI models per wireless function/task have challenged their practical adoption. In this talk, I will discuss these challenges with real-world examples. I will then discuss the emerging paradigm of foundation models and strategies toward achieving such models in the wireless context. Several methods will be presented to effectively represent wireless signals into embeddings that achieve generalizability – a key requirement for the development of foundation AI models. This will be followed with examples of multi-task foundation models developed using pre-training and self-supervised approaches for wireless signals. My talk will conclude with some exciting future research directions toward foundation AI models for 6G networks.

Speaker Biography:
Dr. Hatem Abou-Zeid is an Assistant Professor at the University of Calgary and Director of the WAVES Research Group. His research expertise is in generalizable and trustworthy artificial intelligence (AI) for wireless communications and sensing, and extended reality networking. Prior to joining the University of Calgary, he was at Ericsson Canada leading 5G research for intelligent RANs and low-latency communications. Several wireless access and traffic engineering techniques that he co-invented and co-developed are deployed in 5G networks worldwide. Dr. Abou-Zeid's research has resulted in 20 patent filings and over 80 journals and conference publications in several IEEE flagship venues. He is an avid supporter of industry-university partnerships and applied research, and he served on the Ericsson Government Industry Relations and Talent Development Committees. He delivered numerous invited talks on trustworthy and generalizable AI for future networks and received several accolades including the AI/ML Finalist "Best in Sector" ASTech Award, Best Paper Award at IEEE ICC 2022, Best Student Paper Award at IEEE EMBC 2024, the Schulich Research Excellence Award, Schulich Outstanding Academic Achievement Award, the Software Engineering Professor of the Year Award, and the Schulich Graduate Supervision Award.

Speaker Website and Google Scholar Profile:
https://www.hatem-abouzeid.com/ 
https://scholar.google.com/citations?user=Zf_JnaoAAAAJ&hl=en&oi=ao