Events for May 5, 2026

Title: Generative AI and Deep Learning for Resource Allocation in 6G Wireless NetworksAbstract:This talk provides an in-depth exploration of resource management in 6G wireless networks, focusing on the vision, key performance indicators (KPIs), key enabling techniques (KETs), and the diverse array of services characteristic of these advanced networks. The distinct challenges inherent in 6G resource management call for a pivotal shift toward artificial intelligence (AI) and machine learning (ML)–driven solutions, requiring a departure from traditional optimization-centric <a href="http://approaches.The" target="_blank" title="approaches.The">approaches.The talk sheds light on generative AI and unsupervised ML strategies tailored to effectively address convex and non-convex resource management optimization problems. A key focus is placed on deep unsupervised learning techniques for network resource allocation under nonlinear and non-convex constraints. Deep implicit layers and differentiable projection methods are explored as mechanisms to ensure zero constraint violations in applications such as beamforming, phase-shift optimization, and power <a href="http://allocation.Furthermore" target="_blank" title="allocation.Furthermore">allocation.Furthermore, the potential of generative AI models, including large language models (LLMs), to enable proactive network resource allocation is examined, highlighting their role in optimizing performance and reducing reliance on traditional heuristics. The session concludes by identifying key research gaps and future directions, paving the way for next-generation AI-driven wireless <a href="http://networks.Co-sponsored" target="_blank" title="networks.Co-sponsored">networks.Co-sponsored by: Hong-chuan Yang***CANCELED***Room: 660, Bldg: Engineering/Computer Science Building (ECS), 3800 Finnerty Road, Victoria, British Columbia, Canada, V8P 5C2

Title: Generative AI and Deep Learning for Resource Allocation in 6G Wireless NetworksAbstract:This talk provides an in-depth exploration of resource management in 6G wireless networks, focusing on the vision, key performance indicators (KPIs), key enabling techniques (KETs), and the diverse array of services characteristic of these advanced networks. The distinct challenges inherent in 6G resource management call for a pivotal shift toward artificial intelligence (AI) and machine learning (ML)–driven solutions, requiring a departure from traditional optimization-centric <a href="http://approaches.The" target="_blank" title="approaches.The">approaches.The talk sheds light on generative AI and unsupervised ML strategies tailored to effectively address convex and non-convex resource management optimization problems. A key focus is placed on deep unsupervised learning techniques for network resource allocation under nonlinear and non-convex constraints. Deep implicit layers and differentiable projection methods are explored as mechanisms to ensure zero constraint violations in applications such as beamforming, phase-shift optimization, and power <a href="http://allocation.Furthermore" target="_blank" title="allocation.Furthermore">allocation.Furthermore, the potential of generative AI models, including large language models (LLMs), to enable proactive network resource allocation is examined, highlighting their role in optimizing performance and reducing reliance on traditional heuristics. The session concludes by identifying key research gaps and future directions, paving the way for next-generation AI-driven wireless <a href="http://networks.Co-sponsored" target="_blank" title="networks.Co-sponsored">networks.Co-sponsored by: Hong-chuan YangRoom: 660, Bldg: Engineering/Computer Science Building (ECS), 3800 Finnerty Road, Victoria, British Columbia, Canada, V8P 5C2

IEEE North Saskatchewan Section Meeting - May, 202657 Campus Dr, Saskatoon, Saskatchewan, Canada, S7N 5A9, Virtual: https://events.vtools.ieee.org/m/544435

Future of communication and sensing network is being transformed with the advancement in next generations of wireless with Beyond-5G, beyond-WiFi-8, ICAS, NTN, VR/XR/Metaverse, Digital-Twin and other emerging applications. Higher quality of experiences for connected future with ubiquitous lowest latency and superhigh data rate connectivity services will require innovative wireless technologies and communication hardware combined with AI/ML. Mobile platform integrated RF systems with antenna front ends are common factor for most of the wireless applications. Emerging usage scenarios will need intelligent mobile platforms with ultra-small form-factor, requiring co-design and heterogeneous integration of dis-similar semiconductor device, circuit and antenna technologies, in order to satisfy the desired application-specific performance criteria for the evolving use <a href="http://cases.This" target="_blank" title="cases.This">cases.This presentation will present the emerging technology trends and will focus on the antenna-integrated RF to mm-wave/THz array integrated frontend opportunities and challenges demanding new technology, design, development and integration. Example architectures to enablemultifunction microsystem platform will be <a href="http://discussed.Speaker(s):" target="_blank" title="discussed.Speaker(s):">discussed.Speaker(s): Dr. Debabani Choudhury, Agenda: - 6:30 - 7:00 PM Networking- 7:00 - 8:00 PM Technical TalkBldg: Cal Lutheran Center for Entrepreneurship (Hub101), 31416 Agoura Rd, Westlake Village, California, United States, 91361, Virtual: https://events.vtools.ieee.org/m/494694