rajanie prabha

I am a fourth year PhD student 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 had the opportunity to undertake my Masters thesis as an exchange student at ETH Zurich under the SEMP scholarship, working under the guidance of Prof. Konrad Schindler and Prof. Laura Leal-Taxie. My thesis is available online here.

Email  /  CV  /  Medium  /  Google Scholar  /  Linkedin  /  Github

profile photo
Looking for collaborators, feel free to reach out :)


Publications
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 Tackling Climate Change with Machine Learning (Spotlight), 2025
Solar_inequity
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
Solar_inequity
SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote Sensing
Zhecheng Wang, Rajanie Prabha*, Tianyuan Huang*, Jiajun Wu, Ram Rajagopal
(* equal contribution)
AAAI, 2024
Github
Solar_inequity
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 and Dataset link
Solar_inequity
Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams Using Machine Learning
Manu Tom, Rajanie Prabha, Tianyu Wu, Emmanuel Baltsavias, Laura Leal-Taixé, Konrad Schindler
Remote Sensing MDPI, 2020
Solar_inequity
Lake Ice Monitoring with Webcams and Crowd-Sourced Images
Rajanie Prabha, Manu Tom, Mathias Rothermel, Emmanuel Baltsavias, Laura Leal-Taixé, Konrad Schindler
ISPRS, 2020
Github


Industry Experience

[Google] X, the Moonshot Factory

AI Resident for Tapestry
June 2024-August 2024

Pittsburgh Supercomputing Center, Pittsburgh

Machine Learning Research Scientist
March 2020 - August 2021

Philips Innovation Campus, Bangalore

Software Engineer
June 2016-July 2017

Luminovo Artificial Intelligence, Munich

Student Research Intern
April 2018 - July 2018



Miscellanea
DeepSolar-3M
  • at Sustainability Data Science Conference 2025, Stanford Data Science Center
Generative Editing for Adversarial Attacks @ EEML 2023 | Poster
Invited Talks @ AnitaB.org, 2021 | Presentations
Peer Review Activities
- Advances in Approximate Bayesian Inference (AABI) @ ICLR 2025
- ML Reproducibility Challenge 2022, 2020
- ICBINB @ NeurIPS 2021
- Grace Hopper Celebration (vGHC), AI Track, 2021
- Machine Learning for Physical Sciences 2020, 2019 @ NeurIPS
Service
Women Techmakers Ambassador, Google | 2022 — Present
Women Techmakers Member, Google | 2021 — 2022
Member of AI Committee, AnitaB.org | 2019 — 2024
Course Project Posters
CEE272R, Engineering Future Electricity Systems, Stanford University
CS236, Deep Generative Models, Stanford University
CS330, Deep Multi-Task and Meta Learning, Stanford University
IN2346, Deep Learning for Computer Vision, Technical University Munich

Copyright © Rajanie Prabha 2025 Non-academic Space