Tackling Climate Change with Machine Learning
Priya Donti is a Ph.D. student in Computer Science and Public Policy at Carnegie Mellon University, and a U.S. Department of Energy Computational Science Graduate Fellow. 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. Priya is a recipient of the MIT Technology Review Innovators Under 35 award, 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.