Priya Donti
Assistant Professor
Develops machine learning for forecasting, optimization, and control in high-renewables power grids, incorporating physics and hard constraints into deep learning.
Priya Donti's lab at MIT works on learning theory & optimization and reasoning & neuro-symbolic AI. 7 papers since 2023. 7 PhD students. 15 alumni. Applications close .
At a glance
- papers, 2023–2026
- 2/ year
- at T1 venues
- 0%
- PhD students
- 7
- MS students
- 0
- alumni listed
- 15
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 4 papers2025 · T1 0
- 3 papers2024 · T1 0
- 0 papers2023 · T1 0
T1 venuesOther
Research focuspaper titles that use each topic's words
- Learning theory & optimization3 papers
- Reasoning & neuro-symbolic AI0 papers
- grids0 papers
- power grids0 papers
- constraints0 papers
Paper list
From the lab homepage.
20254 papers
- IEEE Internet ComputingA Vision for Computational Decarbonization of Societal Infrastructure
- International Conference on Autonomous Agents and Multiagent Systems (AAMAS)Improving Policy Optimization via ε-Retrain
- IEEE Transactions on Power SystemsLarge Scale Bilevel Optimization for N-K SCOPF Using Adversarial Robustness
- Tackling Climate Change with Machine Learning Workshop at ICLRPF∆: A Benchmark Dataset for Power Flow with Load, Generator, & Topology Variations
20243 papers
- Climate Change AI ReportGrand Challenge Initiatives in AI for Climate & Nature: Landscape Assessment and Recommendations
- International Conference on Machine Learning (ICML)Position: Application-Driven Innovation in Machine Learning
- An MIT Exploration of Generative AIThe Climate and Sustainability Implications of Generative AI
Where alumni went15 listed
Apply to MITFall 2027
MIT EECS Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- TOEFL/IELTS
- Fee
- USD 90
Confirmed on the program page.
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Data
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- Papers
- The lab homepage
- Members
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