- Program Year: 4
- Academic Institution: Carnegie Mellon University
- Field of Study: Computer Science and Public Policy
- Academic Advisor: Zico Kolter
National Renewable Energy Laboratory (2018)
B.S. Computer Science and Mathematics, Harvey Mudd College, 2015
- Personal URL: http://priyadonti.com
Summary of Research
My work seeks to develop machine learning, optimization, and control methods for robust, emissions-minimal energy system management that are powerful enough to cope with the system's large-scale nature.
Priya L. Donti and J. Zico Kolter. Machine Learning for Sustainable Energy Systems. Forthcoming in the Annual Review of Environment and Resources (2021).
Bingqing Chen*, Priya L. Donti*, Kyri Baker, J. Zico Kolter, Mario Bergés. Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization. Forthcoming at ACM e-Energy (2021).
Priya L. Donti*, David Rolnick*, J. Zico Kolter. DC3: A learning method for optimization with hard constraints. International Conference on Learning Representations (2021).
Priya L. Donti, Melrose Roderick, Mahyar Fazlyab, J. Zico Kolter. Enforcing robust control guarantees within neural network policies. International Conference on Learning Representations (2021).
Po-Wei Wang, Priya L. Donti, Bryan Wilder, and J. Zico Kolter. SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. International Conference on Machine Learning (2019).
Priya L. Donti, Yajing Liu, Andreas J. Schmitt, Andrey Bernstein, Rui Yang, and Yingchen Zhang. Matrix Completion for Low-Observability Voltage Estimation. IEEE Transactions on Smart Grid (2019).
Priya L. Donti, InÃƒÂªs Lima Azevedo, and J. Zico Kolter. How much are we saving after all? Characterizing the effects of commonly-varying assumptions on emissions and damage estimates in PJM. Environmental Science & Technology (2019).
Priya L. Donti, Brandon Amos, and J. Zico Kolter. Task-based End-to-End Model Learning in Stochastic Optimization. Neural Information Processing Systems (2017).
PREPRINTS AND WORKING PAPERS:
David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer Chayes, Yoshua Bengio. Tackling Climate Change with Machine Learning. https://arxiv.org/abs/1906.05433
Priya L. Donti, Ines Lima Azevedo, and J. Zico Kolter. Inverse Optimal Power Flow: Assessing the Vulnerability of Power Grid Data.
National Science Foundation Graduate Research Fellowship, 09/2015 - 08/2017.
Thomas J. Watson Fellowship (National Award), 07/2015-08/2016.
Don Chamberlain Computer Science Research Award (Harvey Mudd College), 05/2015.
Radley Prize in Humanities, Social Sciences, and the Arts (Harvey Mudd College), 05/2015.
Computing Research Association Outstanding Undergraduate Finalist (National Award), 12/2014.
William and Wyllis Leonhard Merit Scholarship (Harvey Mudd College), 10/2014.
Udall Scholarship Honorable Mention (National Award), 04/2014.
Dean Chris Sundberg HMC Leadership Prize (Harvey Mudd College), 05/2013.
Jean and Joseph Platt Prize (Harvey Mudd College), 09/2012.
Harvey Mudd President's Scholarship, 09/2011-05/2015.