Focusing on the Big Picture: Insights into a Systems Approach to Deep Learning for Satellite Imagery. - Ritwik Gupta; Carson D. Sestili; Javier A. Vazquez-Trejo; Matthew E. Gaston (IEEE BigData, 2018)

Open Problems in Robotic Anomaly Detection. - Ritwik Gupta; Zachary T. Kurtz; Sebastian A. Scherer; Jonathon M. Smereka (CoRR, 2018)

Creating xBD: A Dataset for Assessing Building Damage from Satellite Imagery. - Ritwik Gupta; Bryce Goodman; Nirav Patel; Ricky Hosfelt; Sandra Sajeev; Eric T. Heim; Jigar Doshi; Keane Lucas; Howie Choset; Matthew E. Gaston (CVPR Workshops, 2019)

xBD: A Dataset for Assessing Building Damage from Satellite Imagery. - Ritwik Gupta; Richard Hosfelt; Sandra Sajeev; Nirav Patel; Bryce Goodman; Jigar Doshi; Eric T. Heim; Howie Choset; Matthew E. Gaston (CoRR, 2019)

Proceedings of NeurIPS 2019 Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response. - Ritwik Gupta; Eric T. Heim (CoRR, 2020)

Proceedings of NeurIPS 2020 Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response. - Ritwik Gupta; Eric T. Heim; Edoardo Nemni (CoRR, 2020)

WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data. - Rupa Kurinchi-Vendhan; Björn Lütjens; Ritwik Gupta; Lucien Werner; Dava J. Newman (CoRR, 2021)

xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery. - Fernando Paolo; Tsu-ting Tim Lin; Ritwik Gupta; Bryce Goodman; Nirav Patel; Daniel Kuster; David Kroodsma; Jared Dunnmon (NeurIPS, 2022)

Snowpack Estimation in Key Mountainous Water Basins from Openly-Available, Multimodal Data Sources. - Malachy Moran; Kayla Woputz; Derrick Hee; Manuela Girotto; Paolo D'Odorico; Ritwik Gupta; Daniel Feldman; Puya Vahabi; Alberto Todeschini; Colorado J. Reed (CoRR, 2022)

Satlas: A Large-Scale, Multi-Task Dataset for Remote Sensing Image Understanding. - Favyen Bastani; Piper Wolters; Ritwik Gupta; Joe Ferdinando; Aniruddha Kembhavi (CoRR, 2022)

Emerging Technology and Policy Co-Design Considerations for the Safe and Transparent Use of Small Unmanned Aerial Systems. - Ritwik Gupta; Alexander M. Bayen; Sarah Rohrschneider; Adrienne Fulk; Andrew W. Reddie; Sanjit A. Seshia; Shankar Sastry 001; Janet Napolitano (CoRR, 2022)

SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understanding. - Favyen Bastani; Piper Wolters; Ritwik Gupta; Joe Ferdinando; Aniruddha Kembhavi (ICCV, 2023)

Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning. - Colorado J. Reed; Ritwik Gupta; Shufan Li; Sarah Brockman; Christopher Funk; Brian Clipp; Kurt Keutzer; Salvatore Candido; Matt Uyttendaele; Trevor Darrell (ICCV, 2023)

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. - Sungduk Yu; Walter M. Hannah; Liran Peng; Jerry Lin; Mohamed Aziz Bhouri; Ritwik Gupta; Björn Lütjens; Justus C. Will; Gunnar Behrens; Julius Busecke; Nora Loose; Charles Stern; et al. (NeurIPS, 2023)

ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. - Sungduk Yu; Walter M. Hannah; Liran Peng; Mohamed Aziz Bhouri; Ritwik Gupta; Jerry Lin; Björn Lütjens; Justus C. Will; Tom Beucler; Bryce E. Harrop; Benjamin R. Hillman; Andrea M. Jenney; et al. (CoRR, 2023)

Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings. - Sarah Shoker; Andrew W. Reddie; Sarah Barrington; Ruby Booth; Miles Brundage; Husanjot Chahal; Michael Depp; Bill Drexel; Ritwik Gupta; Marina Favaro; Jake Hecla; Alan Hickey; et al. (CoRR, 2023)

Harnessing AI and robotics in humanitarian assistance and disaster response. - Thomas Manzini; Robin R. Murphy; Eric T. Heim; Caleb Robinson; Guido Zarrella; Ritwik Gupta (Sci. Robotics, 2023)

See, Say, and Segment: Teaching LMMs to Overcome False Premises. - Tsung-Han Wu; Giscard Biamby; David M. Chan; Lisa Dunlap; Ritwik Gupta; Xudong Wang 007; Joseph E. Gonzalez; Trevor Darrell (CVPR, 2024)

xT: Nested Tokenization for Larger Context in Large Images. - Ritwik Gupta; Shufan Li; Tyler Zhu; Jitendra Malik; Trevor Darrell; Karttikeya Mangalam (ICML, 2024)

Open-Source Assessments of AI Capabilities: The Proliferation of AI Analysis Tools, Replicating Competitor Models, and the Zhousidun Dataset. - Ritwik Gupta; Leah Walker; Eli Glickman; Raine Koizumi; Sarthak Bhatnagar; Andrew W. Reddie (CoRR, 2024)

Visual Haystacks: Answering Harder Questions About Sets of Images. - Tsung-Han Wu; Giscard Biamby; Jerome Quenum; Ritwik Gupta; Joseph E. Gonzalez; Trevor Darrell; David M. Chan (CoRR, 2024)

Data-Centric AI Governance: Addressing the Limitations of Model-Focused Policies. - Ritwik Gupta; Leah Walker; Rodolfo Corona; Stephanie Fu; Suzanne Petryk; Janet Napolitano; Trevor Darrell; Andrew W. Reddie (CoRR, 2024)

Whack-a-Chip: The Futility of Hardware-Centric Export Controls. - Ritwik Gupta; Leah Walker; Andrew W. Reddie (CoRR, 2024)

Enough Coin Flips Can Make LLMs Act Bayesian. - Ritwik Gupta; Rodolfo Corona; Jiaxin Ge; Eric Wang; Dan Klein 001; Trevor Darrell; David M. Chan (ACL (1), 2025)

Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark. - Tsung-Han Wu; Giscard Biamby; Jerome Quenum; Ritwik Gupta; Joseph E. Gonzalez; Trevor Darrell; David M. Chan (ICLR, 2025)

LISAT: Language-Instructed Segmentation Assistant for Satellite Imagery. - Jerome Quenum; Wen-Han Hsieh; Tsung-Han Wu; Ritwik Gupta; Trevor Darrell; David M. Chan (CoRR, 2025)

REOrdering Patches Improves Vision Models. - Declan Kutscher; David M. Chan; Yutong Bai; Trevor Darrell; Ritwik Gupta (CoRR, 2025)