Hello! I am a Co-founder and Chair of Climate Change AI (CCAI), an initiative to catalyze impactful work at the intersection of climate change and machine learning. I am currently running CCAI through the Runway Startup Postdoc Program, hosted by Cornell Tech and the Jacobs Institute. I will also join MIT EECS as an Assistant Professor in Fall 2023, and am currently recruiting Ph.D. students and postdocs.

My research focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Specifically, my work explores methods to incorporate the physics and hard constraints associated with electric power systems into deep learning models. Please see here for a list of my recent publications.

I am a recipient of the MIT Technology Review’s 2021 “35 Innovators Under 35” award. I was previously a U.S. Department of Energy Computational Science Graduate Fellow, a Siebel Scholar, an NSF Graduate Research Fellow, and a Thomas J. Watson Fellow. I received my Ph.D. from the Computer Science Department and the Department of Engineering & Public Policy at Carnegie Mellon University, co-advised by Zico Kolter and Inês Azevedo. I did my undergraduate degree at Harvey Mudd College, with a major in computer science and math as well as an emphasis in environmental analysis.