BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Talks.cam//talks.cam.ac.uk// X-WR-CALNAME:Talks.cam BEGIN:VEVENT SUMMARY:Self-Supervised Learning\, Unified Sensing &\; Beyond - Aaqib S aeed\, Eindhoven University of Technology DTSTART:20241029T160000Z DTEND:20241029T170000Z UID:TALK219094@talks.cam.ac.uk CONTACT:Cecilia Mascolo DESCRIPTION:**Abstract:** The ubiquity of interconnected systems has given rise to a world enriched with omnipresent computing. The proliferation of devices\, embedded with sophisticated sensors\, generates data at an unpr ecedented scale\, presenting both opportunities and challenges for artific ial intelligence (AI) systems in personal health monitoring. Self-supervis ed learning and decentralized AI are emerging as effective ways to harness the power of distributed data and computing resources\, enabling the deve lopment of predictive models that form the bases of next-generation embedd ed intelligence. This talk will highlight our recent work on addressing th e challenges associated with data-centric federated learning\, developing foundation models\, and unifying large language and sensory models for mod alities\, such as electrocardiograms\, for comprehensive health analysis.\ n\n \n\n**Biography:** Aaqib Saeed is an Assistant Professor of On-body Se nsing and Edge AI at Eindhoven University of Technology (TU/e) and the rec ipient of the prestigious AiNed Fellowship Grant. Prior to this\, he serve d as a Research Scientist in AI at Philips Research. His research interest s include deep learning\, self-supervision\, federated learning\, and audi o understanding for personal health. He received his Ph.D. cum laude from Eindhoven University of Technology. During his PhD\, Aaqib also collaborat ed with renowned researchers at Google Brain through research internships. Currently\, at TU/e\, he is leading a Decentralized AI Research Lab focus ing on developing self-learning systems with applications in healthcare. LOCATION:Computer Lab\, FW11 and Online END:VEVENT END:VCALENDAR