Speaker: Michael (Misha) Chertkov (University of Arizona)

Title: Digital Twins with Brains: Generative AI Meets Physics in Energy Infrastructure Abstract: Operating and planning modern energy infrastructures — electric power, natural gas, transmission and distribution networks — require navigating complex physical flows under uncertainty, incomplete information, and increasingly volatile external conditions. At the same time, recent advances in Generative AI offer new ways to reason, sample, and make decisions in high-dimensional environments. In this talk, I will introduce the sampling-decisions / decision-flow framework, which adapts core principles of state-of-the-art generative models of AI to energy-system challenges. The approach blends physics-based modeling with data-driven sampling, enabling digital twins that are not merely predictive but decision-ready. I will review the methodology and present several illustrative case studies (work in progress and invitation to collaborate) demonstrating how generative-model–based sampling can support operators in real time.