Hina

The unprecedented scale, heterogeneity, and performance requirements of future 6G wireless networks are fundamentally challenging traditional optimization-centric approaches to resource management. These challenges are motivating a paradigm shift toward artificial intelligence (AI)–driven wireless optimization and decision-making frameworks. This lecture explores how deep unsupervised learning and generative AI techniques can be leveraged to solve both convex and non-convex resource allocation problems under complex nonlinear constraints. Particular emphasis is placed on deep unsupervised learning architectures, deep implicit layers, and differentiable projection methods that enable constraint-aware optimization in applications such as beamforming, phase-shift optimization, and power allocation. The lecture further examines the emerging role of generative AI models, including large language models (LLMs), in enabling adaptive, scalable, and environment-aware wireless resource management strategies that reduce dependence on frequent model redesign and retraining. The lecture concludes by discussing key open research challenges and outlining a roadmap toward robust, scalable, and AI-native wireless intelligence for future 6G networks and beyond.

Biography:

Hina Tabassum (Senior Member, IEEE) received the Ph.D. degree from the King Abdullah University of Science and Technology (KAUST). She is currently an Associate Professor with the Lassonde School of Engineering, York University, Canada, where she joined in 2018. She holds the York Research Chair in 5G/6G-Enabled Mobility and Sensing Applications, serves as a Visiting Faculty at the University of Toronto, and was appointed Graduate Program Director of Electrical Engineering and Computer Science at York University in 2026. Her research focuses on the modeling, analysis, and optimization of next-generation wireless communication, localization, and sensing networks. She has co-authored two books, eight book chapters, and over 130 peer-reviewed articles, including 93 journal articles and 42 conference papers in leading IEEE venues. She has delivered more than 20 invited tutorials and talks at international venues on wireless communications and sensing networks. She was selected as an IEEE Communications Society Distinguished Lecturer for 2025–2026 and has been listed among Stanford’s World’s Top 2\% Researchers from 2021 to 2025. Her recognitions include the N2Women STAR (2025), the Early Career Lassonde Innovation Award (2023), and the N2Women Rising Star Award (2022). She is currently an Area Editor for IEEE Open Journal of the Communications Society and IEEE Communications Surveys \& Tutorials, and an Associate Editor for IEEE Transactions on Communications and IEEE Transactions on Wireless Communications.