The inaugural IEEE Power & Energy (PES) Summit on Achieving a More Reliable and Resilient Energy Future will focus on practical experiences by the power and energy industry to achieve a more reliable and resilient electric power grid. The summit will focus on efforts to drive for reliability performance through outage reduction and quicker response. The summit will also include system level thinking to mitigate against high impact low probability or resilience events. Since the summit will be hosted in the west coast a specific topic of reliability and wildfire mitigation will also be covered. The event will include one track technical track (super session format) and not include breakout sessions. The presenters invited are practitioners who will discuss their organizations’ approaches to a more reliable and resilient grid. See the event website for latest schedule and speaker names and topics. Our Bay Area PES and IAS chapters are providing this event notice to publicize it to our Bay Area members. This Summit is sponsored by PG&E and the Power & Energy Society. Our chapter will attend the Summit, and we are providing the Registration link to the PES Summit site, which also names the 20+ speakers and panelists. There are discounts for IEEE and PES members, so we want to point out that Mid-Year PES memberships (for IEEE members) are half off: PES membership for IEEE members: $15.00 Catalog IAS membership for IEEE members: $5.00 Catalog Co-sponsored by: Pacific Gas & Electric Agenda: Monday May19 4:00-7:00 Registration 5:00-7:00 Welcome Reception Tuesday May 20: Registration 7:00 am to 6:00 pm Conference 8:30 am to 5:00 pm 8:30 Welcome & Fireside chat: VP PG&E, Mayor of San Jose 9:30 1: Reliable Energy Delivery: ComEd, Quanta, Oncor 11:00 2: Preventing Catastrophic Outages for Transmission & Substations: PG&E, ComEd, Pepco, Eversource 1:30 3: Data Centers and Their Impact on the Grid (Panel): PG&E, Exelon, Georgia Power, Meta, RTE 3:00 4: Reliability Improvement – Recent Utility Experiences: Challenges, Success Stories, and Lessons Learned: Duke, PG&E, Southern, Quanta 4:00 5: Innovation In Forensics and Failure Analytics: ComEd, Quanta Wednesday May 21: Conference 8:30 am to 3:30 pm 8:30 6: Reliability, Resilience, and Optimization of Capital Investments: PG&E, Duke, NERC 10:00 7: Reliability, Resilience & Wildfire Mitigation: PG&E, OPUC, Sandia 11:00 8: Technology Panel on Reliability: PG&E, Quanta, S&C, Eaton, NuGrid 1:30 9: Climate Resiliency & Major Event Response: Quanta, ComEd, PG&E 2:30 10: Western US Experiences: PG&E, Microsoft, CPUC Bldg: Signia By Hilton San Jose, 170 S. Market St, San Jose, California, United States, 95113

IEEE SCV WIE AI Summit 2025 In an era where AI technologies are rapidly transforming industries and redefining possibilities, it is crucial to explore both the innovations driving this change and the responsibilities that come with it. Today, we will delve into a diverse array of topics that highlight the multifaceted nature of AI and its profound impact on our lives. Our sessions will cover the latest developments in Large Language Models and Foundation Models, exploring efficient fine-tuning, multilingual adaptation, and the role of LLMs as knowledge bases. We will also examine the evolution of AI agents, focusing on autonomous task completion, multi-agent collaboration, and the integration of external knowledge for robust decision-making. In the realm of Vision and Multimodality, we will explore the integration of text, image, and video understanding, as well as advanced techniques like zero-shot learning and self-supervised learning. Our discussions on MLOps for LLMs will provide insights into best practices for training, deploying, and evaluating large models. We will also address the critical areas of Knowledge-Grounded Reasoning, On-Device Learning, and the ethical dimensions of AI, including bias mitigation, privacy preservation, and the detection of misinformation. Talk tracks are broadly classified but not limited to, 1. Large Language Models (LLMs) & Foundation Models Efficient Fine-tuning of LLMs for Low-Resource Languages, LLM Alignment & Instruction-Tuning: Challenges and Advances, Scaling Laws: Understanding Model Size vs. Performance, Multilingual and Cross-Lingual LLM Adaptation, Memory-Augmented LLMs: Enhancing Long-Term Context Understanding, LLMs as Knowledge Bases: Reasoning and Fact-Checking 2. AI Agents Autonomous AI Agents: Leveraging LLMs for Task Completion, Multi-Agent Communication & Collaboration in NLP, Self-Reflective AI: Reflexion and Self-Improvement in Language Models, Hierarchical & Modular AI Agents: Towards Scalable Systems, LLMs as Orchestrators: AI Workflows with Task-Specific Agents, Grounding LLMs in External Knowledge for Robust Decision-Making 3. Vision & Multimodality Vision-Language Models (VLMs): From CLIP to GPT-4V, Multimodal Agents: Integrating Text, Image, and Video Understanding, Spatial and Temporal Reasoning in Vision-Language Models, Zero-Shot and Few-Shot Learning in Multimodal AI, Self-Supervised Learning for Multimodal Representations, Evaluating Multimodal Models: Metrics & Benchmarks, Neurosymbolic Approaches for Language and Vision Tasks 4. MLOps for LLMs LLMOps: Best Practices for Training & Deploying LLMs, Efficient Inference for Large Models: Pruning, Quantization & Distillation, Retrieval-Augmented Generation (RAG): Enhancing Context Awareness, Memory and Context Window Expansion: Architectures & Trade-offs, Evaluation Metrics for LLMs & Conversational Agents 5. Knowledge-Grounded & Reasoning LLMs for Automated Theorem Proving & Scientific Discovery, Commonsense Reasoning in AI Agents, Symbolic vs. Neural Reasoning, Interpretable Models: Improving Explainability in LLMs, Unifying Knowledge Graphs and LLMs for Structured Reasoning 6. On-Device Learning for LLMs and Multi-Modal AI On-Device LLMs & Edge AI for Language Processing and Multimodal Applications, Security, Privacy & Ethical Considerations for On-Device LLMs 7. Ethics, Bias & Fairness Bias Mitigation in Large Language Models, Hallucination Detection & Control in LLMs, Privacy-Preserving NLP: Federated Learning & Differential Privacy, AI and Misinformation: Detecting Deepfakes & Generated Content, Ethical Considerations in Deploying NLP for Real-World Applications Speaker(s): Chloe Ma, Dr. Vishnu S. Pendyala Agenda: 4:00-4:45 Registration / Networking 4:45-5:00 IEEE SCV WIE Welcome Message 5:00-5:15 Keynote Message 5:15-6:00 Charting the AI Landscape by Vishnu Pendyala, Faculty member in Applied Data Science/Academic Senator with San Jose State University 6:00-6:30 Networking and Refreshments 6:30-7:00 Multimodal and Physical AI and their application in Embodied and Robotics Space by Chloe MA, VP ARM 7:00-7:45 Lightning Talks 7:45-8:00 Networking and Wrap-up Bldg: SC9, Intel, 2250 Mission College Blvd, Santa Clara, California, United States, 95054, Virtual: https://events.vtools.ieee.org/m/479108

As neurotechnology advances, the integration of cyber-physical systems (CPS) with neural sensing is opening new frontiers in human augmentation, healthcare, and cognitive computing. However, these systems introduce new security, privacy, and resilience challenges that are often overlooked in traditional CPS security paradigms. This talk will explore the intersection of cyber-physical security and human-in-the-loop neural systems, drawing on recent work in neurosymbolic sensor fusion and real-time, multimodal sensing for closed-loop brain stimulation. We will discuss ongoing research into real-world signal variability, synchronization challenges, privacy risks in shared environments, and adversarial threats to neural inference pipelines. Using deep brain stimulation (DBS) as a case study, we will examine how IoT-integrated neuroscience applications present novel attack surfaces and safety considerations that go beyond traditional CPS security models. We will also highlight our latest work on sensor-based privacy risks, the ethical considerations of AI-mediated neural interventions, and the challenge of aligning security and resilience frameworks with dynamic human behavior. Speaker(s): Luis Garcia Agenda: 6:50 - 7 PM: Registration 7-8 PM: Talk and Q&A Virtual: https://events.vtools.ieee.org/m/484536