Rupa Kurinchi-Vendhan

Rupa Kurinchi-Vendhan

AI for Scientific Discovery and Biodiversity Monitoring

Hello! I am a second-year Ph.D. student at MIT CSAIL, advised by Professor Sara Beery and supported by the NSF Graduate Research Fellowship and the MIT Tina Chan Fellowship. My research focuses on AI for scientific discovery, integrating expert knowledge with remote sensing images and abstract soundscapes to address climate issues such as conservation and biodiversity monitoring. Previously, I received my B.S.c. in Computer Science at the Caltech, where I conducted various remote sensing-based computer vision projects for land cover classification and solar and wind mapping. Aside from academic research, I have completed internships with NASA Langley, Apple, and Coral Gardeners.

Selected Research

BenthIQ: a Transformer-Based Benthic Classification Model for Coral Restoration

Rupa Kurinchi-Vendhan, Drew Gray, Elijah Cole, Pietro Perona
arXiv pre-print arXiv:2311.13661 | 2023

Developed a novel transformer-based neural network capable of multi-label benthic classification, taking processed drone imagery as input and identifying pixels as coral cover, rocks, rubble, sand, algae, etc. This model will be used to inform restoration efforts by providing actionable, specific evidence of where corals should be planted (in areas of higher relative live coral cover).

WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data

Rupa Kurinchi-Vendhan, Björn Lütjens, Ritwik Gupta, Lucien Werner, Dava Newman
NeurIPS CCAI Tackling Climate Change with Machine Learning Workshop | 2021

An accepted paper at the NeurIPS CCAI Tackling Climate Change with Machine Learning 2021 Workshop. We modified existing deep learning-based super-resolution models, and applied them to satellite data to increase the resolution of wind speeds and solar irradiance fields for informing short-term, local energy planning.

Washington, D.C. & Maryland Energy: Estimating Solar Potential Using NASA POWER Data to Inform Renewable Energy Policy

Edward Cronin*, Ashley Fernando*, Jared James*, Rupa Kurinchi-Vendhan*
NASA Technical Reports | 2021

Through NASA's DEVELOP National Program, we worked with the Langley Research Center (LaRC) and partnered with Washington DC's Department of Energy and Environment (DOEE) to create solar potential maps to inform solar panel installation decisions for the District.

Talks

Benthic Classification for Reef Restoration

July 2025: Break Through Tech AI, Massachusetts Institute of Technology
April 2025: Ocean Engineering Seminar, Massachusetts Institute of Technology
November 2023: Berkeley AI Research (BAIR) Climate Initiative, University of Berkeley
November 2023: International Education Week, California Institute of Technology
October 2023: Doris S. Perpall Speaking Competition, California Institute of Technology

Renewable Energy Forecasting

June 2023: WiREDiff: a Wind Resolution-Enhancing Diffusion Model — Advanced Topics in Machine Learning Project Showcase
December 2021: WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data — NeurIPS CCAI Tackling Climate Change with Machine Learning 2021 Workshop Poster Session
November 2021: Estimating Solar Potential Using NASA POWER Data to Inform Renewable Energy Policy for Washington, D.C. — NASA Earth Science DEVELOP National Symposium

Miscellaneous

September 2022: Atlas Packing for Volumetric Rendering — Apple Board of Technology Directors

Teaching

Deep Learning for Ecology

Visiting Lecturer
African Institute of Mathematical Science, Cape Town, South Africa | December 2024

Organized week-long lectures and coding sessions for 10 students on fundamentals of computer vision and its applications in ecology. Assisted students on an object detection-based African Penguin activity heat-mapping pipeline in collaboration with the Two Oceans Aquarium in Cape Town. Course Webpage: https://sites.google.com/aims.ac.za/dl4ecology-course.

Data, Algorithms, and Society

Teaching Assistant
Department of Computing and Mathematical Sciences, California Institute of Technology | September 2023 - March 2024

Taught lectures for 22 students on algorithmic design that avoids bias. Organized and assisted team projects in AI for social good, from refugee monitoring to disaster response planning. Led discussions with teaching staff on student experience and course organization and content.

Learning Systems I & II

Teaching Assistant & Head Teaching Assistant
Department of Computing and Mathematical Sciences, California Institute of Technology | March 2023 - June 2024

Hosted review sessions for 154 students on fundamental topics in machine learning and artificial intelligence. Assist teams to achieve multi-label classification that identify pathologies in chest radiographs. Generated and formatted the radiograph dataset, and created leaderboard for project competition amongst students. Led weekly TA meetings to discuss student progress and plan/organize coursework and assignments.

Outreach

From remote islands to university classrooms, I am committed to sharing my passion for learning and growing across diverse backgrounds. Climate action and scientific advancement require global conversation to ignite equitable, informed progress. Through my research, I hope to bridge the gap between science and civic engagement and aspire to global outreach and impact.

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