Dhruv Shah
rsvha.uedeeh@.dyrulkbeh
I am a Senior Research Scientist at Google DeepMind,
working foundation models of and for robotics.
Previously, I obtained my PhD in EECS at UC Berkeley, where I was advised by Sergey Levine. My
research was 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.
I will join Princeton next academic year as an Assistant Professor in ECE and Robotics! If you are interested in working with me, please apply to the centralized admission portal and mention my name.
CV / Scholar
/ Twitter /
LinkedIn
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Updates
- [Aug 2024] I defended my PhD thesis at Berkeley!
- [July 2024] I started full-time at Google DeepMind Robotics
- [May 2024] NoMaD and RT-X both won the Best Conference Paper
award at ICRA 2024!
- [Mar 2024] I was named a 2024
Microsoft Future Leader in Robotics and AI by the University of Maryland
- [Feb 2024] I will be giving invited talks at MIT, Princeton, UCSD, UCLA, Michigan,
Purdue, and Columbia
- [Jan 2024] NoMaD and RT-X were accepted to ICRA 2024 with 6 best
paper award
nominations!
- [Dec 2023] I will be speaking at the ML4AD
workshop at NeurIPS 2023
- [Nov 2023] I am on the job market! Please reach out if you think I would be a good
fit for your team/department.
- [Oct 2023] Our work on grounding
language models for robotic tasks was accepted to NeurIPS 2023!
- [Oct 2023] Our work on data
collection for social navigation was
accepted to RA Letters and will be presented at ICRA 2024!
- [Sep 2023] We are organizing the 2nd Workshop on Language and Robot
Learning @ CoRL 2023: consider submitting
- [Sep 2023] Three papers to appear at CoRL 2023: a foundation model for visual navigation,
autonomous high-speed off-road driving, and
coming soon!
- [Aug 2023] We are organizing the 6th
Robot Learning Workshop @ NeurIPS 2023: consider submitting
- [Jan 2023] Two papers on generalizable navigation
policies across robots to accepted to ICRA 2023: GNM and Ex-Aug!
- [Jan 2023] We are organizing the 2nd Workshop on Learning from Diverse,
Offline Data at ICRA 2023 — consider submitting
- [Dec 2022] We published an opinion and survey paper on data-driven
navigation!
- [Oct 2022] LM-Nav
was featured in a video by Two Minute Papers!
- [Sep 2022] We are organizing the Workshop on Language and Robot
Learning at CoRL 2022 — consider submitting
- [Sep 2022] Two papers accepted to CoRL 2022: LM-Nav and ReViND!
- [Apr 2022] Our paper on kilometer-scale visual navigation
was accepted to RSS 2022 as a Best Systems Paper Finalist
- [Mar 2022] We are organizing the Workshop on Learning from Diverse,
Offline Data at RSS 2022 — consider submitting
- [Mar 2022] ViKiNG
was featured in the news — see coverage by IEEE Spectrum and ZDNet!
- [Jan 2022] Our paper on skill-centric
state abstractions was accepted to ICLR 2022
- [Jan 2022] Our paper on combining
geometric costmaps with learned models was accepted to ICRA 2022
- [Oct 2021] Check out this blog
post by Sergey on data-driven robot learning, featuring some of my recent research
- [Sep 2021] Our paper on goal-directed exploration on mobile
robots
was accepted as an Oral Presentation to CoRL 2021
- [Aug 2021] I'm teaching the Berkeley Deep RL class (CS285) as Head
GSI this semester
- [May 2021] I'll be spending the summer at Google Brain Robotics, interning with
Brian Ichter and Alex Toshev
- [Feb 2021] Our paper on navigating to visual goals in the
real-world was accepted to ICRA 2021
- [May 2020] Our paper on hybrid control for aerial
manipulation was accepted to RSS 2020
- [Jan 2020] Our paper on analyzing ingredients of real-world RL for
robots was accepted to ICLR 2020
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Projection Design for Compressive Source Separation using Mean Errors and
Cross-Validation
Dhruv Shah,
Ajit Rajwade
International Conference on Image Processing (ICIP), 2019
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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
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