Research Output per Year
Research Output per Year
Overview
Personal Profile
Disclaimer: Any opinions expressed on LinkedIn are the author’s own, made in the author's individual capacity, and do not necessarily reflect the views of NREL.
Saumya Sinha's research interests lie in harnessing deep learning to address climate change impacts and sustainability challenges. At NREL, her research focuses on physics-driven machine learning methods for weather and clean energy applications, such as downscaling and forecasting. She has also worked on exploring machine learning surrogate models for real-world physics problems.
Research Interests
Artificial intelligence for climate change
Foundation models
Operator learning
Professional Experience
Research Intern, Microsoft’s AI for Good Team (2022–2022)
Graduate Research Assistant, University of Colorado Boulder (2021–2023)
Graduate Teaching Assistant, University of Colorado Boulder (2019–2021)
Education/Academic Qualification
Bachelor, Mathematics and Computing, Indian Institute of Technology Kharagpur
PhD, Computer Science, University of Colorado Boulder
Master, Computer Science, University of Colorado Boulder
Fingerprint
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- 1 Similar Profiles
Research Output
- 1 Article
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On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling: Article No. e21
Sinha, S., Benton, B. & Emami, P., 2025, In: Environmental Data Science. 4, 23 p.Research output: Contribution to journal › Article › peer-review
2 Scopus Citations
Awards and Honors
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Annual Grad Students’ Research Expo Award, University of Colorado Boulder
Sinha, S. (Recipient), 2021
Prize: Honorary award
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Outstanding Teaching Assistant Award, University of Colorado Boulder
Sinha, S. (Recipient), 2019
Prize: Honorary award