Magazine Names Fellow as One of 35 Leading Innovators Under 35


Priya Donti, a Department of Energy Computational Science Graduate Fellowship (DOE CSGF) recipient, is one of 35 people named to MIT Technology Review magazine’s list of Innovators Under 35 for 2021. Donti is included as one of nine "visionaries" on the list, recognizing her research into machine learning techniques for energy systems and her leadership in Climate Change AI, a collaboration to apply artificial intelligence technology to slowing and adapting to climate change.

The magazine produces the annual list, featured in the July/August issue posted today, to recognize exceptionally talented inventors, entrepreneurs, visionaries, humanitarians and others who harness technology to improve the world. MIT Technology Review also will feature the honorees at its EmTech MIT conference, an annual event focusing on the year’s most significant developments and their potential business and societal impact. It will be held online September 28-30.

Previous honorees include Google LLC cofounders Larry Page and Sergey Brin and Apple Inc. chief designer Jonathan Ive.

Donti, a fourth-year fellow, is a doctoral candidate working toward a joint degree in computer science and public policy at Carnegie Mellon University. In 2019, she and an international collaboration of researchers, including DOE CSGF recipient Kelly Kochanski, produced an influential 60-page paper, “Tackling Climate Change with Machine Learning,” that described how the technology could be applied across energy, agriculture, forestry and disaster response.

Donti later joined with others to found Climate Change AI, a platform to encourage collaboration and share information on the subject. The organization has held workshops at machine-learning conferences, led educational events at the United Nations Climate Change Conference, and briefed national- and local-level policy makers from several countries. The events have attracted thousands of participants. Climate Change AI also plans to launch a grant program later this year.

At Carnegie Mellon, Donti’s research focuses on applying machine learning to energy systems, especially power grids. Utility operators must constantly balance power production and consumption to avoid overloads and brownouts – a process that is complicated with the addition of variable renewable energy sources, such as wind and solar. Donti studies capturing the physics and constraints behind power grids within AI methods (specifically, deep learning) to improve forecasts and decisions.

After graduation, expected in 2022, Donti plans to continue working on climate change issues through research, entrepreneurship, public policy, or a mix of those options.