Lerrel Pinto

27 papers and 1.2k indexed citations i.

About

Lerrel Pinto is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lerrel Pinto has authored 27 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 18 papers in Control and Systems Engineering and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lerrel Pinto’s work include Reinforcement Learning in Robotics (17 papers), Robot Manipulation and Learning (16 papers) and Domain Adaptation and Few-Shot Learning (6 papers). Lerrel Pinto is often cited by papers focused on Reinforcement Learning in Robotics (17 papers), Robot Manipulation and Learning (16 papers) and Domain Adaptation and Few-Shot Learning (6 papers). Lerrel Pinto collaborates with scholars based in United States, India and Israel. Lerrel Pinto's co-authors include Abhinav Gupta, Abhinav Gupta, Dhiraj Gandhi, James Davidson, Rahul Sukthankar, Pieter Abbeel, Peter Welinder, Wojciech Zaremba, Marcin Andrychowicz and Soumith Chintala and has published in prestigious journals such as arXiv (Cornell University), International Conference on Machine Learning and Neural Information Processing Systems.

In The Last Decade

Co-authorship network of co-authors of Lerrel Pinto i

Fields of papers citing papers by Lerrel Pinto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Countries citing papers authored by Lerrel Pinto

Since Specialization
Citations

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).

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.

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2025