Hello! I am Ph.D. student in Computer Science and Public Policy at Carnegie Mellon University co-advised by Zico Kolter and Inês Azevedo. My research lies at the intersection of machine learning and electric power systems, using algorithmic and policy analytic approaches to promote efficient and low-emission operation of the energy grid. I am funded through the U.S. Department of Energy’s Computational Science Graduate Fellowship and was previously an NSF Graduate Research Fellow.

Before CMU, I was a Thomas J. Watson Fellow traveling the world to study the people, technologies, and policies behind next-generation electricity systems (project blog here). I did my undergrad at Harvey Mudd College in Computer Science/Math with an Emphasis in Environmental Analysis.


  • Task-based End-to-End Model Learning in Stochastic Optimization
    Priya L. Donti, Brandon Amos, and J. Zico Kolter
    Neural Information Processing Systems (NIPS) 2017
    [paper]   [poster]   [video]   [code]
  • Predicting the Quality of User Experiences to Improve Productivity and Wellness (poster)
    Priya L. Donti, Jacob Rosenbloom, Alex Gruver, and James C. Boerkoel Jr.
    Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (2015)
    [poster abstract]