Keisuke Koyama
- Biomedical Engineering top 10%
- Control and Systems Engineering top 5%
- Cognitive Neuroscience top 10%
- Mechanical Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Makoto ShimojoAiguo MingMasatoshi IshikawaYosuke SuzukiWeiwei WanKensuke HaradaTaku SenooHiroaki HASEGAWA
- Topics
- Robot Manipulation and Learning (32 papers)Soft Robotics and Applications (15 papers)Robotic Path Planning Algorithms (7 papers)
- Journals
- SHILAP Revista de lepidopterologíaPhysical review. B, Condensed matterIEEE Access
- Partner nations
- JapanUnited StatesFrance
In The Last Decade
Keisuke Koyama
52 papers receiving 557 citations
Peers
Comparison fields: 5 of 60
- Biomedical Engineering 281
- Control and Systems Engineering 280
- Cognitive Neuroscience 124
- Mechanical Engineering 110
- Computer Vision and Pattern Recognition 79
Countries citing papers authored by Keisuke Koyama
This map shows the geographic impact of Keisuke Koyama'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 Keisuke Koyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keisuke Koyama more than expected).
Fields of papers citing papers by Keisuke Koyama
This network shows the impact of papers produced by Keisuke Koyama. 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 Keisuke Koyama. The network helps show where Keisuke Koyama may publish in the future.
Co-authorship network of co-authors of Keisuke Koyama
This figure shows the co-authorship network connecting the top 25 collaborators of Keisuke Koyama. A scholar is included among the top collaborators of Keisuke Koyama based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Keisuke Koyama. Keisuke Koyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 17 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 9 | |
| 7 | 5 | |
| 8 | 0 | |
| 9 | 89 | |
| 10 | 8 | |
| 11 | 5 | |
| 12 | 13 | |
| 13 | 13 | |
| 14 | 1 | |
| 15 | 4 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 0 | |
| 20 | 2 |
About Keisuke Koyama
Keisuke Koyama is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering and Biomedical Engineering, having authored 57 papers that have together received 586 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (32 papers), Soft Robotics and Applications (15 papers) and Robotic Path Planning Algorithms (7 papers). The work is most often cited by research in Control and Systems Engineering (280 citations), Human-Computer Interaction (45 citations) and Cognitive Neuroscience (124 citations). Keisuke Koyama has collaborated with scholars based in Japan, United States and France. Frequent co-authors include Makoto Shimojo, Aiguo Ming, Masatoshi Ishikawa, Yosuke Suzuki, Weiwei Wan, Kensuke Harada, Taku Senoo, Hiroaki HASEGAWA, Björn Hein and Stephan Mühlbacher-Karrer. Their work appears in journals such as SHILAP Revista de lepidopterología, Physical review. B, Condensed matter and IEEE Access.
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.