Priya Donti, Carnegie Mellon University | Tackling Climate Change with Machine Learning
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About the talk: Climate change is one of the greatest challenges that society faces today, requiring rapid action from all corners. In this talk, Donti will describe how machine learning can be a potentially powerful tool for addressing climate change, when applied in coordination with policy, engineering, and other areas of action. From energy to agriculture to disaster response, she will describe high impact problems where machine learning can help through avenues such as distilling decision-relevant information, optimizing complex systems, and accelerating scientific experimentation. Donti will then dive into some of her own work in this area, which merges data-driven approaches with physical knowledge to facilitate the transition to low-carbon electric power grids.
About the speaker: Priya Donti is a Ph.D. Candidate in Computer Science and Public Policy at Carnegie Mellon University. She is also a co-founder and chair of Climate Change AI, an initiative to catalyze impactful work in climate change and machine learning. Her work focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Specifically, her research explores methods to incorporate the physics and hard constraints associated with electric power systems into deep learning models. Donti is a member of the MIT Technology Review's 2021 list of "35 Innovators Under 35," and is a recipient of 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.
Recent Related Publications
- Tackling Climate Change with Machine Learning
- Machine Learning for Sustainable Energy Systems
- Additional publications
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