Explainable and Robust AI for 6G

Join us for an IEEE ComSoc Distinguished Lecture!

The IEEE Toronto Communications Chapter is pleased to host Professor Sinem Coleri for an engaging talk on “Explainable and Robust AI for 6G” as part of her Canadian lecture tour, which will also be hosted by the Toronto, Kingston, and Ottawa Chapters. Join us to explore cutting-edge insights into AI-driven next-generation <a href="http://networks.

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Talk Abstract:

Unlike previous generations of wireless networks, which were primarily designed to meet the requirements of human communications, 5G networks enable extensive data collection from machines. As we transition to 6G, the emphasis moves beyond connectivity toward leveraging this machine-generated data for a new spectrum of control applications, such as UAV swarms, collaborative robots, and cooperative autonomous vehicles. Designing communication systems for these advanced control applications introduces a distinct set of challenges. These include meeting stringent requirements for delay and reliability, addressing the semantics of control systems, and ensuring robust resource management. In the first part of this talk, we explore ultra-reliable channel modeling and communication techniques based on the integration of extreme value theory with generative AI. These methods offer improved accuracy in predicting rare but critical events while providing adaptivity to dynamic scenarios. In the second part of the talk, we explore the benefits of employing optimization theory based, explainable, and robust AI in radio resource management for the joint design of control and communication systems. These approaches offer a systematic methodology to enhance robustness and interpret decisions made by black-box AI <a href="http://models.

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Room: 4th Floor (BA 4164), Bldg: Bahen Centre for Information Technology, University of Toronto, Toronto, Ontario, Canada, M4Y1R5