EECS Special Seminar: Priya Donti "Optimization-in-the-loop AI for energy and climate"
, Carnegie Mellon U.
Date: Thursday, March 17, 2022
Time: 11:00 AM to 12:00 PM Note: all times are in the Eastern Time Zone
Location: Grier A (34-401A)
Host: Rajeev Ram, EECS
Contact: Chadwick Collins, email@example.com
Speaker URL: None
TALK: EECS Special Seminar: Priya Donti "Optimization-in-the-loop AI for energy and climate"
Addressing climate change will require concerted action across society, including the development of innovative technologies. While methods from artificial intelligence (AI) and machine learning (ML) have the potential to play an important role, these methods often struggle to contend with the physics, hard constraints, and complex decision-making processes that are inherent to many climate and energy problems. To address these limitations, I present the framework of “optimization-in-the-loop AI,” and show how it can enable the design of AI models that explicitly capture relevant constraints and decision-making processes. For instance, this framework can be used to design learning-based controllers that provably enforce the stability criteria or operational constraints associated with the systems in which they operate. It can also enable the design of task-based learning procedures that are cognizant of the downstream decision-making processes for which a model’s outputs will be used. By significantly improving performance and preventing critical failures, such techniques can unlock the potential of AI and ML for operating low-carbon power grids, improving energy efficiency in buildings, and addressing other high-impact problems of relevance to climate action.
Priya Donti is a Ph.D. Candidate in Computer Science and Public Policy at Carnegie Mellon University. Her research explores methods to incorporate physics and hard constraints into deep learning models, in order to enable their use for forecasting, optimization, and control in high-renewables power grids. She is also a co-founder and chair of Climate Change AI, an initiative to catalyze impactful work in climate change and machine learning. Priya is a recipient of the MIT Technology Review’s 2021 “35 Innovators Under 35” award, the Siebel Scholarship, the U.S. Department of Energy Computational Science Graduate Fellowship, and best paper awards at ICML (honorable mention), ACM e-Energy (runner-up), PECI, the Duke Energy Data Analytics Symposium, and the NeurIPS workshop on AI for Social Good.
Host: Rajeev Ram
Created by Fern D Keniston at Thursday, March 03, 2022 at 10:13 PM.