Graylin Jay
Impact in
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- Robotics and Automated Systems
- Robot Manipulation and Learning
- Software top 10%
Papers in
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- Robot Manipulation and Learning 4
- Robotics and Automated Systems 4
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- Modular Robots and Swarm Intelligence 3
- Teleoperation and Haptic Systems 2
- Co-authors
- Odest Chadwicke Jenkins (8 shared papers)Sarah Osentoski (8 shared papers)Christopher Crick (7 shared papers)Benjamin Pitzer (4 shared papers)David P. Hale (1 shared paper)Charles B. Ward (1 shared paper)Nicholas A. Kraft (1 shared paper)Joanne E. Hale (1 shared paper)
- Journals
- International Journal of Social Robotics (1 paper)Springer tracts in advanced robotics (1 paper)National Conference on Artificial Intelligence (1 paper)Journal of Software Engineering and Applications (1 paper)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Graylin Jay
9 papers receiving 403 citations
Peers
Comparison fields: 5 of 49
- Control and Systems Engineering 244
- Software 44
- Computer Science Applications 38
- Computer Vision and Pattern Recognition 90
- Mechanical Engineering 156
Countries citing papers authored by Graylin Jay
This map shows the geographic impact of Graylin Jay'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 Graylin Jay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Graylin Jay more than expected).
Fields of papers citing papers by Graylin Jay
This network shows the impact of papers produced by Graylin Jay. 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 Graylin Jay. The network helps show where Graylin Jay may publish in the future.
Co-authors
The 11 scholars most cited alongside Graylin Jay, 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 | 2016 | 144 | |
| 2 | 2009 | 61 | |
| 3 | 2011 | 44 | |
| 4 | 2012 | 43 | |
| 5 | 2011 | 41 | |
| 6 | 2010 | 35 | |
| 7 | 2012 | 31 | |
| 8 | 2012 | 23 | |
| 9 | Brown ROS package: Reproducibility for shared experimentation and learning from demonstration | 2010 | 4 |
About Graylin Jay
Graylin Jay is a scholar working on Control and Systems Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 9 papers that have together received 426 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (4 papers), Robotics and Automated Systems (4 papers), Modular Robots and Swarm Intelligence (3 papers), Reinforcement Learning in Robotics (2 papers), Experimental Learning in Engineering (2 papers), Teleoperation and Haptic Systems (2 papers), Soft Robotics and Applications (1 paper) and Electrowetting and Microfluidic Technologies (1 paper). The work is most often cited by research in Control and Systems Engineering (244 citations), Software (44 citations), Computer Science Applications (38 citations), Computer Vision and Pattern Recognition (90 citations) and Mechanical Engineering (156 citations). Graylin Jay has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Odest Chadwicke Jenkins, Sarah Osentoski, Christopher Crick, Benjamin Pitzer, David P. Hale, Charles B. Ward, Nicholas A. Kraft, Joanne E. Hale, Randy Smith and Daniel H. Grollman. Their work appears in journals such as International Journal of Social Robotics, Springer tracts in advanced robotics, National Conference on Artificial Intelligence and Journal of Software Engineering and Applications.
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.