Describe how GPUs Accelerating genomics on AI/ ML. Speaker Bio Speaker Bio: Dr. Hari Sadasivan is a Sr AI Performance Engineer at NVIDIA, an affiliate assistant professor at the University of Washington, Seattle, and a Distinguished Visitor of the IEEE Computer Society. Hari’s research focuses on accelerating genomics and AI for drug discovery on GPUs. Previously, Hari led the AMD Center of Excellence in AI at UW Seattle and co-founded the AMD lifesciences group. Hari received his PhD and Masters in CSE from the University of Michigan Ann Arbor and worked at Samsung R&D before. Speaker(s): , Hari Sadasivan Agenda: Room: 629, Bldg: Bannan, 901 12th Ave, , Seattle , Washington, United States, 98122, Virtual: https://events.vtools.ieee.org/m/499863

Describe how GPUs Accelerating genomics on AI/ ML. Speaker Bio Speaker Bio: Dr. Hari Sadasivan is a Sr AI Performance Engineer at NVIDIA, an affiliate assistant professor at the University of Washington, Seattle, and a Distinguished Visitor of the IEEE Computer Society. Hari’s research focuses on accelerating genomics and AI for drug discovery on GPUs. Previously, Hari led the AMD Center of Excellence in AI at UW Seattle and co-founded the AMD lifesciences group. Hari received his PhD and Masters in CSE from the University of Michigan Ann Arbor and worked at Samsung R&D before. This is a Hybrid Event Link is on the event site Speaker(s): , Hari Sadasivan Agenda: Room: 629, Bldg: Bannan, 901 12th Ave, , Seattle , Washington, United States, 98122, Virtual: https://events.vtools.ieee.org/m/499866

Free Registration (with a Zoom account; you can get one for free if you don't already have it. This requirement is to avoid Zoom bombing. Please sign in using the email address tied to your Zoom account — not necessarily the one you used to register for the event.): https://sjsu.zoom.us/meeting/register/i6n2sgjLQFelwXCNz4-YGQ Synopsis: As large language models (LLMs) evolve from static, prompt-based tools into autonomous, agentic systems capable of reasoning, planning, and acting with minimal human oversight, organizations face an exciting yet complex frontier. These advanced systems hold the potential to revolutionize enterprise workflows, developer tools, and customer-facing applications—but realizing that potential requires navigating a host of technical and ethical challenges. This panel brings together leading voices from AI research, infrastructure engineering, and real-world application domains to discuss how agentic LLM systems are moving from lab experiments to production-grade deployments. Panelists will explore critical topics such as orchestration, safety, observability, and evaluation, while offering hard-earned lessons from deploying these systems at scale. Whether you're building tools for developers, integrating LLM agents into enterprise pipelines, or shaping the next wave of intelligent products, this discussion will equip you with the strategic and technical know-how to bring agentic AI into impactful, everyday use. Don’t miss this opportunity to learn what it truly takes to operationalize the future of AI. --------------------------------------------------------------- By registering for this event, you agree that IEEE and the organizers are not liable to you for any loss, damage, injury, or any incidental, indirect, special, consequential, or economic loss or damage (including loss of opportunity, exemplary or punitive damages). The event will be recorded and will be made available for public viewing. Speaker(s): Yubin Kim, Gautam Solaimalai, Shaleen Kumar Gupta, Vishal Jain, Abhay Khosla, Rahul Raja, Harsh Varshney Virtual: https://events.vtools.ieee.org/m/494702