Dhruv Shah
rsvha.uedeeh@.dyrulkbeh

I am a Senior Research Scientist at Google DeepMind, working foundation models of and for robotics. Concurrently, I am finishing up my PhD in EECS at UC Berkeley, where I am advised by Sergey Levine. My research is supported by the Berkeley Fellowship for Graduate Study, and has been nominated for (and received) several Best Paper Awards at leading robotics conferences, including RSS and ICRA.

Earlier, I graduated with honors from IIT Bombay, where I received the Undergraduate Research Award and the Institute Academic Prize. I have also been fortunate to spend time at Meta AI (FAIR), Google DeepMind (Brain Robotics), Carnegie Mellon University, Imperial College London and the University of Sydney.

CV / Scholar / Twitter / LinkedIn

Updates

Blog Posts

Publications

Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Open X-Embodiment Collaboration

Best Conference Paper Award
Best Student Paper Award (Finalist)
Best Paper Award in Robot Manipulation (Finalist)
International Conference on Robotics and Automation (ICRA), 2024
CoRL 2023 Workshop Towards Generalist Robots   (Oral Presentation)

arXiv / Blog Post / Dataset / Code

NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration

Ajay Sridhar, Dhruv Shah, Catherine Glossop, Sergey Levine

Best Conference Paper Award
Best Student Paper Award (Finalist)
Best Paper Award in Cognitive Robotics (Finalist)
International Conference on Robotics and Automation (ICRA), 2024
CoRL 2023 Workshop on Pre-Training for Robot Learning   (Oral Presentation)
NeurIPS 2023 Workshop on Foundation Models for Decision-Making   (Oral Presentation)

arXiv / Summary Video / Dataset / Code

SACSoN: Scalable Autonomous Data Collection for Social Navigation

Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine

Robotics and Automation Letters (RA-L), 2023
International Conference on Robotics and Automation (ICRA), 2024
Conference on Robot Learning (CoRL), 2023   (Live Demo)

arXiv / Summary Video / Dataset

Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control

Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, Brian Ichter

Advances in Neural Information Processing Systems (NeurIPS) 2023

arXiv / Summary Video

ViNT: A Foundation Model for Visual Navigation

Dhruv Shah, Ajay Sridhar, Nitish Dashora, Kyle Stachowicz, Kevin Black, Noriaki Hirose, Sergey Levine

Conference on Robot Learning (CoRL), 2023   (Oral Presentation & Live Demo)
Bay Area Machine Learning Symposium (BayLearn) 2022   (Oral Presentation)

arXiv / Summary Video / Code

FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing

Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar, Ilya Kostrikov, Sergey Levine

Conference on Robot Learning (CoRL), 2023

arXiv / Summary Video / Code / Media Coverage 1, 2, 3, 4

Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning

Dhruv Shah, Michael Equi, Blazej Osinski, Fei Xia, Brian Ichter, Sergey Levine

Conference on Robot Learning (CoRL), 2023

arXiv / Summary Video / Code / Interactive Colab

ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation

Noriaki Hirose, Dhruv Shah, Ajay Sridhar, Sergey Levine

International Conference on Robotics and Automation (ICRA), 2023

arXiv / Summary Video

GNM: A General Navigation Model to Drive Any Robot

Dhruv Shah, Ajay Sridhar, Arjun Bhorkar, Noriaki Hirose, Sergey Levine

International Conference on Robotics and Automation (ICRA), 2023

arXiv / Summary Video / Code / Media Coverage

Learning Robotic Navigation from Experience: Principles, Methods, and Recent Results

Sergey Levine, Dhruv Shah

Philosophical Transactions of the Royal Society B, 2022   (Invited Paper)

arXiv

Offline Reinforcement Learning for Visual Navigation

Dhruv Shah, Arjun Bhorkar, Hrish Leen, Ilya Kostrikov, Nick Rhinehart, Sergey Levine

Conference on Robot Learning (CoRL), 2022   (Oral Presentation)

arXiv / Talk @ CoRL / Code

LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action

Dhruv Shah, Blazej Osinski, Brian Ichter, Sergey Levine

Conference on Robot Learning (CoRL), 2022
Foundation Models for Decision Making Workshop at NeurIPS 2022   (Oral Presentation)
Bay Area Machine Learning Symposium (BayLearn) 2022   (Oral Presentation)

arXiv / Summary Video / Code / Interactive Colab / 2MP Feature / Spotlight @ CoRL / Media Coverage

ViKiNG: Vision-Based Kilometer-Scale Navigation with Geographic Hints

Dhruv Shah, Sergey Levine

Best Systems Paper Finalist
Robotics: Science and Systems (RSS), 2022   (Oral Presentation)

arXiv / Summary Video / Talk @ RSS / Media Coverage 1, 2, 3

Hybrid Imitative Planning with Geometric and Predictive Costs in Off-road Environments

Nitish Dashora, Daniel Shin, Dhruv Shah, Henry Leopold, David Fan, Ali Agha-Mohammadi, Nicholas Rhinehart, Sergey Levine

International Conference on Robotics and Automation (ICRA), 2022

arXiv / Talk @ ICRA

Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning

Dhruv Shah, Peng Xu, Yao Lu, Ted Xiao, Alexander Toshev, Sergey Levine, Brian Ichter

International Conference on Learning Representations (ICLR), 2022

Blog Post / arXiv / Talk @ ICLR

Rapid Exploration for Open-World Navigation with Latent Goal Models

Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine

Conference on Robot Learning (CoRL), 2021   (Oral Presentation)
Workshop on Never-Ending Reinforcement Learning at ICLR 2021   (Oral Presentation)

Blog Post / arXiv / Talk @ CoRL / Talk @ ICLR / Dataset / Media Coverage

ViNG: Learning Open-World Navigation with Visual Goals

Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine

International Conference on Robotics and Automation (ICRA), 2021

arXiv / Summary Video

Aerial Manipulation Using Hybrid Force and Position NMPC Applied to Aerial Writing

Dimos Tzoumanikas, Felix Graule, Qingyue Yan, Dhruv Shah, Marija Popovic, Stefan Leutenegger

Robotics: Science and Systems (RSS), 2020

arXiv / Talk @ RSS / Cool Demos

The Ingredients of Real World Robotic Reinforcement Learning

Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine

International Conference on Learning Representations (ICLR), 2020   (Spotlight Presentation)

Blog Post / arXiv / Talk / Virtual Presentation

Swarm Aggregation Without Communication and Global Positioning

Dhruv Shah, Leena Vachhani

Robotics and Automation Letters (RA-L), 2019
International Conference on Robotics and Automation (ICRA), 2019

Projection Design for Compressive Source Separation using Mean Errors and Cross-Validation

Dhruv Shah, Ajit Rajwade
International Conference on Image Processing (ICIP), 2019

Designing Constrained Projections for Compressed Sensing: Mean Errors and Anomalies with Coherence

Dhruv Shah, Alankar Kotwal, Ajit Rajwade
Global Conference on Signal and Information Processing (GlobalSIP), 2018