Noah Brown
Impact in
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- Robot Manipulation and Learning
- Robotics and Automated Systems
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- AI-based Problem Solving and Planning
- Speech and dialogue systems
Papers in
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- Robot Manipulation and Learning 2
- Robotics and Automated Systems 1
- Control and Dynamics of Mobile Robots 1
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- AI-based Problem Solving and Planning 1
- Reinforcement Learning in Robotics 1
- Co-authors
- Zhuo Xu (1 shared paper)Fei Xia (1 shared paper)Dorsa Sadigh (1 shared paper)Karthik Mahadevan (1 shared paper)Carolina Parada (1 shared paper)Leila A. Takayama (1 shared paper)Andy Zeng (1 shared paper)
- Journals
- arXiv (Cornell University) (2 papers)ACM/IEEE International Conference on Human-Robot Interaction (HRI) (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Noah Brown
5 papers receiving 540 citations
Noah Brown's Hit Papers
Peers
Comparison fields: 5 of 37
- Control and Systems Engineering 365
- Artificial Intelligence 214
- Computer Vision and Pattern Recognition 63
- Social Psychology 42
- Health Informatics 3
Countries citing papers authored by Noah Brown
This map shows the geographic impact of Noah Brown'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 Noah Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Noah Brown more than expected).
Fields of papers citing papers by Noah Brown
This network shows the impact of papers produced by Noah Brown. 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 Noah Brown. The network helps show where Noah Brown may publish in the future.
Co-authors
The 7 scholars most cited alongside Noah Brown, 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 | RT-1: Robotics Transformer for Real-World Control at Scale Hit paper breakdown → | 2023 | 416 |
| 2 | π₀: A Vision-Language-Action Flow Model for General Robot Control Hit paper breakdown → | 2025 | 97 |
| 3 | 2024 | 31 | |
| 4 | 2023 | 11 | |
| 5 | 2022 | 2 |
About Noah Brown
Noah Brown is a scholar working on Control and Systems Engineering, Artificial Intelligence, Social Psychology, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 5 papers that have together received 557 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (2 papers), Social Robot Interaction and HRI (1 paper), AI-based Problem Solving and Planning (1 paper), Robotics and Automated Systems (1 paper), Reinforcement Learning in Robotics (1 paper) and Control and Dynamics of Mobile Robots (1 paper). The work is most often cited by research in Control and Systems Engineering (365 citations), Artificial Intelligence (214 citations), Computer Vision and Pattern Recognition (63 citations), Social Psychology (42 citations) and Health Informatics (3 citations). Noah Brown has collaborated with scholars based in United States and Canada. Frequent co-authors include Zhuo Xu, Fei Xia, Dorsa Sadigh, Karthik Mahadevan, Carolina Parada, Leila A. Takayama and Andy Zeng. Their work appears in journals such as arXiv (Cornell University) and ACM/IEEE International Conference on Human-Robot Interaction (HRI).
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.