Chelsea Finn

About

Chelsea Finn is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Chelsea Finn has authored 77 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Artificial Intelligence, 28 papers in Computer Vision and Pattern Recognition and 26 papers in Control and Systems Engineering. Recurrent topics in Chelsea Finn’s work include Reinforcement Learning in Robotics (38 papers), Domain Adaptation and Few-Shot Learning (27 papers) and Robot Manipulation and Learning (26 papers). Chelsea Finn is often cited by papers focused on Reinforcement Learning in Robotics (38 papers), Domain Adaptation and Few-Shot Learning (27 papers) and Robot Manipulation and Learning (26 papers). Chelsea Finn collaborates with scholars based in United States, Canada and United Kingdom. Chelsea Finn's co-authors include Sergey Levine, Pieter Abbeel, Trevor Darrell, Julian Ibarz, Jie Tan, Peter Pástor, Mrinal Kalakrishnan, Xin Tan, Yan Duan and Kelvin Xu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and The International Journal of Robotics Research.

In The Last Decade

Co-authorship network of co-authors of Chelsea Finn i

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Fields of papers citing papers by Chelsea Finn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chelsea Finn. 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 Chelsea Finn. The network helps show where Chelsea Finn may publish in the future.

Countries citing papers authored by Chelsea Finn

Since Specialization

Citations

This map shows the geographic impact of Chelsea Finn'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 Chelsea Finn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chelsea Finn 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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