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Lerrel Pinto
NYU professor whose lab works on scalable robot learning, from self-supervised grasping to low-cost data collection in real homes.
New York University · United States
- Rank
- #153
- Score
- 37.5
- Citations
- 5,160
- h-index
- 32
- Robotics papers 2023–2025
- 10
Source: OpenAlex author record, as of 2026-10-19. How we rank
About
Lerrel Pinto's early work on self-supervised grasping showed that robots can learn from tens of thousands of their own attempts. His NYU lab builds low-cost tools for collecting robot training data in real homes.
Representative work
Selected highly cited papers, linked to their publisher or arXiv versions:
- Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours (2016)
- Robust Adversarial Reinforcement Learning (2017)
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration 0 (2024)
Links
Who is Lerrel Pinto?
Lerrel Pinto is an NYU professor whose lab works on scalable robot learning, from self-supervised grasping to low-cost data collection in real homes.