Jun Kinugawa
Impact in
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- Robot Manipulation and Learning
- Robotic Mechanisms and Dynamics
Papers in
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- Robot Manipulation and Learning 28
- Robotic Mechanisms and Dynamics 7
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- Prosthetics and Rehabilitation Robotics 9
- Soft Robotics and Applications 8
- Muscle activation and electromyography studies 6
- Co-authors
- Kazuhiro Kosuge (47 shared papers)Ronnapee Chaichaowarat (4 shared papers)Shogo Arai (10 shared papers)Diego Páez-Granados (3 shared papers)Hiroshi Nakano (3 shared papers)Yusuke Sugahara (2 shared papers)Yasufumi Tanaka (2 shared papers)Jiaqi Miao (2 shared papers)
In The Last Decade
Jun Kinugawa
43 papers receiving 507 citations
Peers
Comparison fields: 5 of 67
- Control and Systems Engineering 287
- Industrial and Manufacturing Engineering 77
- Computer Vision and Pattern Recognition 136
- Biomedical Engineering 194
- Rehabilitation 24
Countries citing papers authored by Jun Kinugawa
This map shows the geographic impact of Jun Kinugawa'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 Jun Kinugawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Kinugawa more than expected).
Fields of papers citing papers by Jun Kinugawa
This network shows the impact of papers produced by Jun Kinugawa. 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 Jun Kinugawa. The network helps show where Jun Kinugawa may publish in the future.
Co-authors
The 14 scholars most cited alongside Jun Kinugawa, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 89 | |
| 2 | 2017 | 56 | |
| 3 | 2018 | 40 | |
| 4 | 2019 | 32 | |
| 5 | 2017 | 28 | |
| 6 | 2012 | 28 | |
| 7 | 2017 | 24 | |
| 8 | 2018 | 24 | |
| 9 | 2020 | 22 | |
| 10 | 2018 | 21 | |
| 11 | 2016 | 14 | |
| 12 | 2014 | 13 | |
| 13 | 2018 | 12 | |
| 14 | 2015 | 8 | |
| 15 | 2014 | 8 | |
| 16 | 2016 | 8 | |
| 17 | 2019 | 7 | |
| 18 | 2021 | 7 | |
| 19 | 2021 | 6 | |
| 20 | 2015 | 6 |
About Jun Kinugawa
Jun Kinugawa is a scholar working on Control and Systems Engineering, Biomedical Engineering, Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition and Mechanical Engineering, having authored 48 papers that have together received 520 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (28 papers), Advanced Manufacturing and Logistics Optimization (11 papers), Robotic Path Planning Algorithms (10 papers), Prosthetics and Rehabilitation Robotics (9 papers), Soft Robotics and Applications (8 papers), Robotic Mechanisms and Dynamics (7 papers), Muscle activation and electromyography studies (6 papers) and Teleoperation and Haptic Systems (6 papers). The work is most often cited by research in Control and Systems Engineering (287 citations), Industrial and Manufacturing Engineering (77 citations), Computer Vision and Pattern Recognition (136 citations), Biomedical Engineering (194 citations) and Rehabilitation (24 citations). Jun Kinugawa has collaborated with scholars based in Japan, Hong Kong and Pakistan. Frequent co-authors include Kazuhiro Kosuge, Ronnapee Chaichaowarat, Shogo Arai, Diego Páez-Granados, Hiroshi Nakano, Yusuke Sugahara, Yasufumi Tanaka, Jiaqi Miao, Diyi Liu and Yasuhisa Hirata. Their work appears in journals such as IEEE Transactions on Robotics, Sensors, Advanced Robotics, IEEE Robotics and Automation Letters and IEEE Transactions on Human-Machine Systems.
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.