Lerrel Pinto

Welcome!

I am an Assistant Professor of Computer Science at NYU Courant working on problems in Robotics and Machine Learning. I am also affiliated with the Center for Data Science. Together with several wonderful colleagues I am part of the CILVR (Computational Intelligence, Learning, Vision and Robotics) group.

My lab’s goal is to get robots to generalize and adapt in the diverse world we live in. To this end, my research touches the areas of Robot Learning, Representation Learning, Reinforcement Learning, and Affordable Robotics.

Recent News

Recent Talks

Here are some public talks that covers my recent research:

Courses Taught at NYU

Selected Research and Publications


From play to policy: Conditional behavior generation from uncurated robot data
From play to policy: Conditional behavior generation from uncurated robot data
Jeff Cui, Yibin Wang, Mahi Shafiullah, Lerrel Pinto
In ICLR (Notable Top-5% Paper / Oral Presentation)
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Holo-Dex: Teaching Dexterity with Immersive Mixed Reality
Holo-Dex: Teaching Dexterity with Immersive Mixed Reality
Sridhar Pandian Arunachalam, Irmak Güzey, Soumith Chintala, Lerrel Pinto
In ICRA 2023
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Behavior Transformers: Cloning k modes with one stone
Behavior Transformers: Cloning k modes with one stone
Mahi Shafiullah, Jeff Cui, Ariuntuya Altanzaya, Lerrel Pinto
In NeurIPS 2022 (Nominated for Outstanding Paper Award)
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Watch and Match: Supercharging Imitation with Regularized Optimal Transport
Watch and Match: Supercharging Imitation with Regularized Optimal Transport
Siddhant Haldar, Vaibhav Mathur, Denis Yarats, Lerrel Pinto
In CoRL 2022 (Best Paper Award Finalist)
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Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation
Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation
Sridhar Pandian Arunachalam, Sneha Silwal, Ben Evans, Lerrel Pinto
In ICRA 2023
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Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning
Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto
Preprint
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The Surprising Effectiveness of Representation Learning for Visual Imitation
The Surprising Effectiveness of Representation Learning for Visual Imitation
Jyothish Pari, Nur Muhammad Shafiullah, Sridhar Pandian Arunachalam, Lerrel Pinto
In RSS 2022
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Context is Everything: Implicit Identification for Dynamics Adaptation
Context is Everything: Implicit Identification for Dynamics Adaptation
Ben Evans, Abitha Thankaraj, Lerrel Pinto
In ICRA 2022
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Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
In ICLR 2022
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Reinforcement Learning with Prototypical Representations
Reinforcement Learning with Prototypical Representations
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
In ICML 2021
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Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency
Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency
Qiang Zhang, Tete Xiao, Alexei A. Efros, Lerrel Pinto, Xiaolong Wang
In ICLR 2021 (Oral Presentation)
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Self-Supervised Policy Adaptation during Deployment
Self-Supervised Policy Adaptation during Deployment
Nicklas Hansen, Rishabh Jangir, Yu Sun, Guillem Alenya, Pieter Abbeel, Alexei A. Efros, Lerrel Pinto, Xiaolong Wang
In ICLR 2021 (Spotlight Presentation)
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Task-Agnostic Morphology Evolution
Task-Agnostic Morphology Evolution
Donald J. Hejna III, Pieter Abbeel, Lerrel Pinto
In ICLR 2021
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Visual Imitation Made Easy
Visual Imitation Made Easy
Sarah Young, Dhiraj Gandhi, Shubham Tulsiani, Abhinav Gupta, Pieter Abbeel, Lerrel Pinto
In CoRL 2020
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Learning Predictive Representations for Deformable Objects Using Contrastive Estimation
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation
Wilson Yan, Ashwin Vangipuram,, Pieter Abbeel, Lerrel Pinto
In CoRL 2020
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Robust Policies via Mid-Level Visual Representations
Robust Policies via Mid-Level Visual Representations
Bryan Chen, Alexander Sax, Francis E. Lewis, Silvio Savarese, Jitendra Malik, Amir Zamir, Lerrel Pinto
In CoRL 2020
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Automatic Curriculum Learning through Value Disagreement
Automatic Curriculum Learning through Value Disagreement
Yunzhi Zhang, Pieter Abbeel, Lerrel Pinto
In NeurIPS 2020
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Generalized Hindsight for Reinforcement Learning
Generalized Hindsight for Reinforcement Learning
Alexander Li, Lerrel Pinto, Pieter Abbeel
In NeurIPS 2020
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Reinforcement Learning with Augmented Data
Reinforcement Learning with Augmented Data
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
In NeurIPS 2020 (Spotlight Presentation)
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Learning to Manipulate Deformable Objects without Demonstrations
Learning to Manipulate Deformable Objects without Demonstrations
Yilin Wu, Wilson Yan, Thanard Kurutach, Lerrel Pinto, Pieter Abbeel
In RSS 2020
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Swoosh! Rattle! Thump! - Actions that Sound
Swoosh! Rattle! Thump! - Actions that Sound
Dhiraj Gandhi, Abhinav Gupta, Lerrel Pinto
In RSS 2020
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Hierarchically Decoupled Imitation for Morphological Transfer
Hierarchically Decoupled Imitation for Morphological Transfer
Donald J. Hejna III, Pieter Abbeel, Lerrel Pinto
In ICML 2020
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Discovering Motor Programs by Recomposing Demonstrations
Discovering Motor Programs by Recomposing Demonstrations
Tanmay Shankar, Shubham Tulsiani, Lerrel Pinto, Abhinav Gupta
In ICLR 2020
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Robot Learning via Human Adversarial Games
Robot Learning via Human Adversarial Games
Jiali Duan, Qian Wang, Lerrel Pinto, C.-C. Jay Kuo, Stefanos Nikolaidis
In IROS 2019 (Best Cognitive Robotics Paper Award Finalist)
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PyRobot: An Open-source Robotics Framework for Research and Benchmarking
PyRobot: An Open-source Robotics Framework for Research and Benchmarking
Adithya Murali, Tao Chen, Kalyan Vasudev Alwala, Dhiraj Gandhi, Lerrel Pinto, Saurabh Gupta, Abhinav Gupta
Open source platform (https://www.pyrobot.org/)
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Environment Probing Interaction Policies
Environment Probing Interaction Policies
WenXuan Zhou, Lerrel Pinto, Abhinav Gupta
In ICLR 2019
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Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation
Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation
Pratyusha Sharma, Lekha Mohan, Lerrel Pinto, Abhinav Gupta
In CoRL 2018
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Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
Abhinav Gupta, Adithya Murali, Dhiraj Gandhi, Lerrel Pinto
In NeurIPS 2018
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Asymmetric Actor Critic for Image-Based Robot Learning
Asymmetric Actor Critic for Image-Based Robot Learning
Lerrel Pinto, Marcin Andrychowicz, Peter Welinder, Wojciech Zaremba, Pieter Abbeel
In RSS 2018
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CASSL: Curriculum Accelerated Self-Supervised Learning
CASSL: Curriculum Accelerated Self-Supervised Learning
Adithyavairavan Murali, Lerrel Pinto, Dhiraj Gandhi, Abhinav Gupta
In ICRA 2018
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Learning to Fly by Crashing
Learning to Fly by Crashing
Dhiraj Gandhi, Lerrel Pinto, Abhinav Gupta
In IROS 2017
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Robust Adversarial Reinforcement Learning
Robust Adversarial Reinforcement Learning
Lerrel Pinto, James Davidson, Rahul Sukthankar, Abhinav Gupta
In ICML 2017
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Learning to Push by Grasping: Using multiple tasks for effective learning
Learning to Push by Grasping: Using multiple tasks for effective learning
Lerrel Pinto, Abhinav Gupta
In ICRA 2017
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Supervision via Competition: Robot Adversaries for Learning Tasks
Supervision via Competition: Robot Adversaries for Learning Tasks
Lerrel Pinto, James Davidson, Abhinav Gupta
In ICRA 2017
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The Curious Robot: Learning Visual Representations via Physical Interactions
The Curious Robot: Learning Visual Representations via Physical Interactions
Lerrel Pinto, Dhiraj Gandhi, Yuanfeng Han, Yong-Lae Park, Abhinav Gupta
In ECCV 2016 (Spotlight Presentation)
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Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hours
Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hours
Lerrel Pinto, Abhinav Gupta
In ICRA 2016 (Best Student Paper Award)
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