Lerrel Pinto
Impact in
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- Robot Manipulation and Learning
- Human-Computer Interaction top 5%
- Hand Gesture Recognition Systems
Papers in
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- Robot Manipulation and Learning 19
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- Reinforcement Learning in Robotics 16
- Domain Adaptation and Few-Shot Learning 4
- Adversarial Robustness in Machine Learning 3
- Topic Modeling 2
- Co-authors
- Abhinav GuptaDhiraj GandhiJames DavidsonRahul SukthankarSoumith ChintalaBen EvansChris PaxtonNur Muhammad Mahi Shafiullah
- Journals
- arXiv (Cornell University) (6 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2 papers)International Conference on Learning Representations (1 paper)Neural Information Processing Systems (2 papers)
- Partner nations
- United StatesIndiaChina
In The Last Decade
Lerrel Pinto
31 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 78
- Control and Systems Engineering 772
- Human-Computer Interaction 123
- Computer Vision and Pattern Recognition 405
- Artificial Intelligence 477
- Aerospace Engineering 201
Countries citing papers authored by Lerrel Pinto
This map shows the geographic impact of Lerrel Pinto's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lerrel Pinto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lerrel Pinto more than expected).
Fields of papers citing papers by Lerrel Pinto
This network shows the impact of papers produced by Lerrel Pinto. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lerrel Pinto. The network helps show where Lerrel Pinto may publish in the future.
Co-authors
The 25 scholars most cited alongside Lerrel Pinto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 13 | |
| 4 | 2024 | 21 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 49 | |
| 7 | 2023 | 16 | |
| 8 | 2023 | 45 | |
| 9 | 2022 | 1 | |
| 10 | 2021 | 7 | |
| 11 | Discovering Motor Programs by Recomposing Demonstrations | 2020 | 9 |
| 12 | Visual Imitation Made Easy | 2020 | 1 |
| 13 | Reinforcement Learning with Augmented Data | 2020 | 9 |
| 14 | Learning Predictive Representations for Deformable Objects Using Contrastive Estimation | 2020 | 7 |
| 15 | Robust Policies via Mid-Level Visual Representations: An Experimental Study in Manipulation and Navigation | 2020 | 1 |
| 16 | Automatic Curriculum Learning through Value Disagreement | 2020 | 2 |
| 17 | 2020 | 19 | |
| 18 | 2019 | 3 | |
| 19 | 2017 | 158 | |
| 20 | Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours Hit paper breakdown → | 2016 | 590 |
About Lerrel Pinto
Lerrel Pinto is a scholar working on Control and Systems Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science Applications and Human-Computer Interaction, having authored 35 papers that have together received 1.2k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (19 papers), Reinforcement Learning in Robotics (16 papers), Human Pose and Action Recognition (6 papers), Multimodal Machine Learning Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Adversarial Robustness in Machine Learning (3 papers), Soft Robotics and Applications (3 papers) and Topic Modeling (2 papers). The work is most often cited by research in Control and Systems Engineering (772 citations), Human-Computer Interaction (123 citations), Computer Vision and Pattern Recognition (405 citations), Artificial Intelligence (477 citations) and Aerospace Engineering (201 citations). Lerrel Pinto has collaborated with scholars based in United States, India and China. Frequent co-authors include Abhinav Gupta, Abhinav Gupta, Dhiraj Gandhi, James Davidson, Rahul Sukthankar, Soumith Chintala, Ben Evans, Chris Paxton, Nur Muhammad Mahi Shafiullah and Arthur Szlam. Their work appears in journals such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), International Conference on Learning Representations and Neural Information Processing Systems.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.