Daniel S. Brown
Impact in
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- Distributed Control Multi-Agent Systems
Papers in
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- Reinforcement Learning in Robotics 8
- Adversarial Robustness in Machine Learning 3
- Anomaly Detection Techniques and Applications 3
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- Distributed Control Multi-Agent Systems 8
- Co-authors
- Michael A. Goodrich (6 shared papers)Matthew Johnson (1 shared paper)Ashwin Balakrishna (5 shared papers)Ken Goldberg (5 shared papers)Scott Niekum (4 shared papers)Gaurav Datta (1 shared paper)Anca D. Dragan (2 shared papers)Lee M. Seversky (1 shared paper)
- Journals
- Journal of Biomechanics (1 paper)Nature (1 paper)International Journal of Cancer (1 paper)SHILAP Revista de lepidopterología (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesPuerto RicoRomania
In The Last Decade
Daniel S. Brown
34 papers receiving 224 citations
Peers
Comparison fields: 5 of 63
- Computer Science Applications 21
- Computer Networks and Communications 77
- Computer Vision and Pattern Recognition 56
- Artificial Intelligence 80
- Human-Computer Interaction 13
Countries citing papers authored by Daniel S. Brown
This map shows the geographic impact of Daniel S. 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 Daniel S. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel S. Brown more than expected).
Fields of papers citing papers by Daniel S. Brown
This network shows the impact of papers produced by Daniel S. 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 Daniel S. Brown. The network helps show where Daniel S. Brown may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel S. 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
Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 25 | |
| 2 | 2012 | 25 | |
| 3 | 2015 | 21 | |
| 4 | 2014 | 19 | |
| 5 | 1962 | 19 | |
| 6 | 2021 | 19 | |
| 7 | 2013 | 11 | |
| 8 | 2016 | 10 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 9 | |
| 11 | 2024 | 8 | |
| 12 | 2016 | 8 | |
| 13 | 2014 | 8 | |
| 14 | 2006 | 7 | |
| 15 | 2021 | 7 | |
| 16 | Risk-Aware Active Inverse Reinforcement Learning | 2018 | 6 |
| 17 | Monadic Memoization Mixins | 2006 | 6 |
| 18 | 2022 | 5 | |
| 19 | 2022 | 4 | |
| 20 | 2022 | 4 |
About Daniel S. Brown
Daniel S. Brown is a scholar working on Artificial Intelligence, Computer Networks and Communications, Control and Systems Engineering, Biomedical Engineering and Computer Vision and Pattern Recognition, having authored 38 papers that have together received 252 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (8 papers), Distributed Control Multi-Agent Systems (8 papers), Robot Manipulation and Learning (7 papers), Modular Robots and Swarm Intelligence (5 papers), Slime Mold and Myxomycetes Research (5 papers), Adversarial Robustness in Machine Learning (3 papers), Human Pose and Action Recognition (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Computer Science Applications (21 citations), Computer Networks and Communications (77 citations), Computer Vision and Pattern Recognition (56 citations), Artificial Intelligence (80 citations) and Human-Computer Interaction (13 citations). Daniel S. Brown has collaborated with scholars based in United States, Puerto Rico and Romania. Frequent co-authors include Michael A. Goodrich, Matthew Johnson, Ashwin Balakrishna, Ken Goldberg, Scott Niekum, Gaurav Datta, Anca D. Dragan, Lee M. Seversky, Matthew Berger and Ryan Hoque. Their work appears in journals such as Journal of Biomechanics, Nature, International Journal of Cancer, SHILAP Revista de lepidopterología and arXiv (Cornell University).
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.