Priya Donti is assistant professor and the Silverman (1968) Family Career Development Professor at MIT EECS and LIDS. She is a co-founder and Chair of Climate Change AI, a global nonprofit initiative to catalyze impactful work at the intersection of climate change and machine learning. Donti's research focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Methodologically, this entails exploring ways to incorporate relevant physics, hard constraints, and decision-making procedures into deep learning workflows. She is a recipient of the MIT Technology Review’s 2021 “35 Innovators Under 35” award and the 2022 ACM SIGEnergy Doctoral Dissertation Award. Previously, she was a Runway Startup Postdoc at Cornell Tech and the Jacobs Institute. She received her Ph.D. from the Computer Science Department and the Department of Engineering & Public Policy at Carnegie Mellon University (CMU), co-advised by Zico Kolter and Inês Azevedo. At CMU, she held the U.S. Department of Energy Computational Science Graduate Fellowship, the Siebel Scholarship, and the NSF Graduate Research Fellowship. Before starting my Ph.D., she was a Thomas J. Watson Fellow, traveling the world to study the people, technologies, and policies behind next-generation electricity systems. She received her undergraduate degree from Harvey Mudd College, with a major in computer science and math as well as an emphasis in environmental analysis.