Priya Donti

  • Program Year: 2
  • Academic Institution: Carnegie Mellon University
  • Field of Study: Computer Science and Public Policy
  • Academic Advisor: Zico Kolter
  • Practicum(s):
    National Renewable Energy Laboratory (2018)
  • Degree(s):
    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.

Publications

Priya L. Donti, Brandon Amos, and J. Zico Kolter. Task-based End-to-End Model Learning in Stochastic Optimization. Neural Information Processing Systems (NIPS) 2017.

How much are we saving after all? An assessment of uncertainty in marginal emissions and damages in PJM. (under review)

Matrix Completion for Low-Observability Voltage Estimation (working paper)

Awards

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.