rajanie prabha

I am a PhD candidate at Stanford University, advised by Prof. Ram Rajagopal in the Civil and Environmental Engineering Department.

I am broadly interested in leveraging machine learning for power grid research, specifically focusing on spatial mapping of grid assets, equity in resource distribution, and grid optimization.

Before joining Stanford, I earned my Bachelor of Technology in Computer Engineering from the National Institute of Technology, Kurukshetra, and later completed my Master of Science in Informatics at the Technical University of Munich, Germany. I also undertook my Masters thesis as an exchange student at ETH Zurich under the SEMP scholarship, working under Prof. Konrad Schindler and Prof. Laura Leal-TaixΓ©. MS thesis is available here.

Email: rajanie [at] stanford [dot] edu

Rajanie Prabha
Working Papers
WECC transmission study
Rethinking transmission scarcity Rajanie Prabha, Liang Min, Ram Rajagopal
Working paper, 2026
ArcGIS StoryMap
Press: Stanford, Public Power, World Economic Forum, Yahoo Finance, NW Council, Utility Dive
Publications
SolarCast distribution
Where Solar Surges Next: Distribution-Planning Forecasts from Zero-Inflated Neural Models Rajanie Prabha, Chad Zanocco, Zhecheng Wang, June Flora, Ram Rajagopal
ACM E-Energy, 2026
DeepSolar AE
Nationwide insights on solar deployment trends and spatial inequalities revealed by vision transformer models Rajanie Prabha, Zhecheng Wang, Chad Zanocco, June Flora, Ram Rajagopal
Applied Energy, 2026
DeepSolar-3M
DeepSolar-3M: An AI-Enabled Solar PV Database Documenting 3 Million Systems Across the US Rajanie Prabha, Zhecheng Wang, Chad Zanocco, June Flora, Ram Rajagopal
ICLR Workshop TCCML, 2025
Spotlight, Best Paper Award
GitHub, πŸ€— Dataset
Non-residential solar
Exploring the Potential of Non-Residential Solar to Tackle Energy Injustice Moritz Wussow, Chad Zanocco, Zhecheng Wang, Rajanie Prabha, June Flora, Dirk Neumann, Arun Majumdar, Ram Rajagopal
Nature Energy, 2024
Press: Stanford, TechXplore
SkyScript
SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote Sensing Zhecheng Wang, Rajanie Prabha*, Tianyuan Huang*, Jiajun Wu, Ram Rajagopal
AAAI, 2024  (* equal contribution)
GitHub
MiikeMineStamps
MiikeMineStamps: A Long-Tailed Dataset of Japanese Stamps via Active Learning Paola A. Buitrago, Evgeny Toropov, Rajanie Prabha, Julian Uran, Raja Adal
ICDAR, 2021
GitHub, Dataset
Lake ice satellites
Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams Using Machine Learning Manu Tom, Rajanie Prabha, Tianyu Wu, Emmanuel Baltsavias, Laura Leal-TaixΓ©, Konrad Schindler
Remote Sensing MDPI, 2020
Lake ice webcams
Lake Ice Monitoring with Webcams and Crowd-Sourced Images Rajanie Prabha, Manu Tom, Mathias Rothermel, Emmanuel Baltsavias, Laura Leal-TaixΓ©, Konrad Schindler
ISPRS, 2020
GitHub
Industry Experience
Selected Talks & Posters
Peer Review
Teaching & Leadership
Course Project Posters