Posts by Collection



Open Problems in Robotic Anomaly Detection

Ritwik Gupta, Zachary T. Kurtz, Sebastian Scherer, Jonathon M. Smereka

Venue: arXiv preprint

Motivated by the development of ROS 2, this work discusses open problems in the field of robotic anomaly detection and presents an inverse reinforcement learning-based approach to detecting anomalous motion.

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

Venue: 2018 IEEE International Conference on Big Data

Focused around the IARPA Functional Map of the World Challenge, this work discusses how to scale deep learning at an academic lab for geospatial analysis.

Creating xBD: A Dataset for Assessing Building Damage from Satellite Imagery

Ritwik Gupta, Bryce Goodman, Nirav Patel, Ricky Hosfelt, Sandra Sajeev, Eric Heim, Jigar Doshi, Keane Lucas, Howie Choset, Matthew Gaston

Venue: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2019

Preliminary work discussing xBD, the foundational dataset for assessing building damage after natural disasters from very-high resolution satellite imagery with over 850,000 annotations across 45,000 square kilometers.

xBD: A Dataset for Assessing Building Damage from Satellite Imagery

Ritwik Gupta, Richard Hosfelt, Sandra Sajeev, Nirav Patel, Bryce Goodman, Jigar Doshi, Eric Heim, Howie Choset, Matthew Gaston

Venue: arXiv preprint

The foundational dataset for assessing building damage after natural disasters from very-high resolution satellite imagery with over 850,000 annotations across 45,000 square kilometers.

Region-level Active Detector Learning

Michael Laielli, Giscard Biamby, Dian Chen, Ritwik Gupta, Adam Loeffler, Phat Dat Nguyen, Ross Luo, Trevor Darrell, Sayna Ebrahimi

Venue: arXiv preprint

A new strategy that subsumes previous Image-level and Object-level approaches into a generalized, Region-level approach.

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

Rupa Kurinchi-Vendhan, Björn Lütjens, Ritwik Gupta, Lucien Werner, Dava Newman

Venue: Climate Change AI Workshop at NeurIPS 2021

An extensible benchmark of deep learning-based super-resolution techniques on wind and solar data. We accompany the benchmark with a novel public, processed, and machine learning-ready dataset for benchmarking super-resolution methods on wind and solar data.

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

Venue: CVPR 2022 Workshop on Multimodal Learning for Earth and Environment

We fuse satellite and weather data to estimate snowpack depth in key mountainous regions and beat single-source estimation by 5.0 inches RMSE.

Satlas: A Large-Scale, Multi-Task Dataset for Remote Sensing Image Understanding

Favyen Bastani, Piper Wolters, Ritwik Gupta, Joe Ferdinando, Aniruddha Kembhavi

Venue: International Conference on Computer Vision (ICCV) 2023

A foundational remote sensing dataset with over 290M labels under 137 categories and seven label modalities for pre-training large machine learning models.

xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery

Ritwik Gupta*, Fernando Paolo*, Tsu-ting Tim Lin*, Bryce Goodman, Nirav Patel, Daniel Kuster, David Kroodsma, Jared Dunnmon

Venue: NeurIPS 2022

The largest labeled dataset for training ML models to detect and characterize vessels and ocean structures in synthetic aperture radar imagery. xView3 is built to help control illegal, unreported, and unregulated fishing.

Emerging Technology and Policy Co-Design Considerations for the Safe and Transparent Use of Small Unmanned Aerial Systems

Ritwik Gupta, Alexander Bayen, Sarah Rohrschneider, Adrienne Fulk, Andrew Reddie, Sanjit A. Seshia, Shankar Sastry, Janet Napolitano

Venue: Center for Security in Politics, UC Berkeley

With the meteoric rise of small unmanned aerial systems, we discuss policy shortcomings in integrating sUAS technology in a safe fashion into our society. We suggest technology and policy co-design approaches to addressing these gaps in our systems.

Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning

Ritwik Gupta*, Colorado Reed*, Shufan Li*, Sarah Brockman, Christopher Funk, Brian Clipp, Kurt Keutzer, Salvatore Candido, Matt Uyttendaele, Trevor Darrell

Venue: International Conference on Computer Vision (ICCV) 2023

A pre-training method to make encoders robust to imagery captured at varying satellite resolutions. State-of-the-art multi-scale pre-training method and the largest satellite imagery foundation model, to date.

Orbital hypersonic delivery systems threaten strategic stability

Ritwik Gupta

Venue: The Bulletin of Atomic Scientists

We assess that China's development of a fractional orbital hypersonic delivery system, combining hypersonic glide vehicles with orbital bombardment, presents a concerning challenge to global stability, allowing for faster, undetectable delivery of large nuclear payloads and signaling renewed interest in first-strike capabilities.

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, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, Nathan M. Urban, Janni Yuval, Guang J. Zhang, Tian Zheng, Michael S. Pritchard

Venue: Neural Information Processing Systems (NeurIPS) 2023

The largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers.

Accelerating the Evolution of AI Export Controls

Ritwik Gupta and Andrew Reddie

Venue: Tech Policy Press

Current US AI hardware export controls are based on the best AI accelerator chip available at that time. This presents wide loopholes which allow adversarial nations to still maintain their capabilities. We propose an alternate way to set export control thresholds based on the analysis of specific ML workloads.

Proliferate, Don’t Obliterate: How Responsive Launch Marginalizes Anti-Satellite Capabilities

Ritwik Gupta and Andrew Reddie

Venue: War on the Rocks

We analyze how the emerging responsive launch industry fundamentally shifts the strategic calculus of ASAT weapons.

See, Say, and Segment: Teaching LMMs to Overcome False Premises

Tsung-Han Wu, Giscard Biamby, David Chan, Lisa Dunlap, Ritwik Gupta, Xudong Wang, Joseph E. Gonzalez, Trevor Darrell

Venue: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024

A method to prevent large, multimodal models (LMMs) to stop hallucinating when given false premises.

LAION and the Challenges of Preventing AI-Generated CSAM

Ritwik Gupta

Venue: Tech Policy Press

I examined the challenges in preventing AI-generated Child Sexual Abuse Material (CSAM), such as within the widely-used LAION-5B dataset, emphasizing the need for updated legal and technological strategies to tackle the spread of such content by generative AI technologies.

Russian Nuclear ASAT Weapons: The Fallout

Sarthak Bhatnagar, Eli Glickman, Bethany Goldblum, Ritwik Gupta, Kaitlyn Lenkeit, Jane Darby Menton, Andrew Neciuk, Andrew Reddie, Vishwaa Sofat, Leah Walker

Venue: Lawfare

What is the state of the existing space governance regime amid concerns that Moscow is developing a nuclear-tipped anti-satellite weapon in orbit?

xT: Nested Tokenization for Larger Context in Large Images

Ritwik Gupta*, Shufan Li*, Tyler Zhu*, Jitendra Malik, Trevor Darrell, Karttikeya Mangalam

Venue: International Conference on Machine Learning (ICML) 2024

xT is a framework which lets you model extremely large images (upwards of 30,000 x 30,000 pixels) end-to-end on contemporary GPUs. You get higher accuracy with fewer parameters and less memory used per region.

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

Venue: arXiv preprint

China is training machine learning models to target American and Allied navel vessels, but how well do they work? In this paper, we train a state-of-the-art machine learning model on a leaked Chinese dataset that labels Aegis combat system components on military vessels. We propose a new methodology for open source assessment of adversary AI capabilities.



Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post. Read more

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post. Read more