#38: Algorithmic Decisions & Power and Sustainability

"What always needs to be at the forefront: what physical and regulatory constraints is your system contending with at any given time and how do you design a suite of methods that actually satisfy those constraints" — Priya L. Donti Priya L. Donti is a Ph.D. student in the Computer Science Department and the Department of Engineering & Public Policy at Carnegie Mellon University, co-advised by Zico Kolter and Inês Azevedo . She is also co-founder and chair of Climate Change AI , an initiative to catalyze impactful work at the intersection of climate change and machine learning. Her work focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Specifically, Priya's research 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 her recent publications. Priya is a member of the MIT Technology Review 2021 list of 35 Innovators Under 35 , and a 2022 Siebel Scholar. She was previously a U.S. Department of Energy Computational Science Graduate Fellow , an NSF Graduate Research Fellow, and a Thomas J. Watson Fellow . Priya received her undergraduate degree at Harvey Mudd College in computer science and math with an emphasis in environmental analysis. *** For show notes and past guests, please visit If you have questions, please email us at contact@aiasiapacific.org or

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#38: Algorithmic Decisions & Power and Sustainability is an episode from AI Asia Pacific Institute Podcast by AI Asia Pacific Institute.

This episode is 00:42:55 long.

This episode was published on Nov 1, 2021.

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