Panel 1
Grid Reformation for AI Data Centers
Moderated by William Hogan, this discussion examined how grid infrastructure must adapt to escalating AI data-center demand.
Past event
On May 20, 2025, Harvard SEAS convened researchers, industry leaders, and policy experts for the first Power and AI Symposium, followed by an executive short course on May 21.
Overview
The Harvard SEAS coverage described the event as part of the initiative’s broader work to integrate artificial intelligence with power systems in ways that support sustainable and efficient energy solutions.
Panel themes
Panel 1
Moderated by William Hogan, this discussion examined how grid infrastructure must adapt to escalating AI data-center demand.
Panel 2
Moderated by Henry Lee, the panel explored changing regulatory, business, and market conditions shaped by AI integration into power systems.
Panel 3
Moderated by Minlan Yu, the conversation focused on redesigning AI infrastructure across the stack to improve energy efficiency.
Panel 4
Moderated by Francesca Dominici, the final panel addressed how AI can support grid modernization, operations, and system optimization.
Symposium schedule
Panelists: Arin Kaye (EPRI), Lane Dilg (OpenAI), Carole-Jean Wu (Meta), Tongxin Zheng (ISO New England)
Panelists: Erik Belz (Engine No.1), Keith Benes (formerly DOE), Pearl Donohoo-Vallett (FERC), Howard Gugel (NERC)
Panelists: Jeffrey Burns (IBM), Esha Choukse (Microsoft), Christos Kozyrakis (Nvidia), Houle Gan (Google)
Panelists: Asim Fazlagic (Eversource Energy), Prashant Kansal (ERCOT), Taiil Kim (Schneider Electric), Xing Wang (AWS)
Conleigh Byers (Harvard), Noman Bashir (MIT), Jae-Won Chung (University of Michigan), Yize Chen (University of Alberta), Sarah Keren (Technion), Yicheng Zhu (UC Berkeley)
Accompanying short course
The following day, Harvard SEAS offered Power Systems and Artificial Intelligence: An Introduction, a one-day program designed to help power-system engineers and AI practitioners build a shared technical language.
The SEAS article highlighted the short course as a bridge between grid operations, AI applications for power systems, and energy-efficient AI infrastructure.
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