Hello! I am the co-founder and Executive Director of Climate Change AI (CCAI), a global nonprofit 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 at Cornell Tech and the Jacobs Institute. I will also join MIT EECS as an Assistant Professor in Fall 2023.
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 workflows. 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 and of the 2022 ACM SIGEnergy Doctoral Dissertation 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.