Stanford Energy Student Lectures - AI Enhanced Battery Modeling, Community Solar Policy, and AI-Driven Materials Discovery

Join us as grad student/postdoc speakers from various technical areas deliver short and accessible presentations about their innovative clean energy research. Learn more about cutting-edge science and the most recent breakthroughs in areas such as renewables, energy conversion materials and devices, catalysis, and decarbonization from the researchers themselves! Refreshments will be provided starting at 2:45pm. Share your feedback on the speakers for a chance to win a Coupa gift card! Speaker Topics: Xiaoyu Yang - Bridging Physics, Data, and Learning in Lithium Battery Modeling Abstract: Battery modeling plays a critical role in the design, control, and safety of next-generation energy storage systems, yet significant challenges remain in achieving both physical fidelity and computational scalability across multiple length scales. This presentation discusses a research framework that integrates physics-based modeling, observation-driven correction, and machine learning to address these challenges. The work spans electrochemical transport within porous electrodes, state estimation under model uncertainty, and scalable surrogate modeling for battery systems operating under thermal gradients. A dual-continuum electrochemical transport formulation is introduced to capture transport-limited behavior beyond conventional electrode assumptions. The presentation also examines how indirect measurements can be combined with imperfect models to improve estimation of internal battery states, particularly core temperature. In addition, a machine-learning-based surrogate framework is presented for efficiently modeling coupled electrochemical–thermal interactions in multilevel battery systems. Together, these studies demonstrate how physics, data, and learning can be combined to develop accurate, efficient, and scalable battery models for applications including fast charging, thermal management, diagnostics, and large-scale battery system optimization. Speaker bio: Xiaoyu Yang is a