Shun Kiyono
- Artificial Intelligence top 5%
- Mechanical Engineering top 10%
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 10%
- Biomedical Engineering
- Co-authors
- Jun SuzukiWei GaoKentaro InuiPeisen S. HuangMasato MitaSho TakaseTomoya MizumotoMasahiro Kaneko
- Topics
- Natural Language Processing Techniques (14 papers)Topic Modeling (13 papers)Advanced Measurement and Metrology Techniques (12 papers)
- Partner nations
- JapanUnited States
In The Last Decade
Shun Kiyono
34 papers receiving 583 citations
Peers
Comparison fields: 5 of 55
- Artificial Intelligence 263
- Mechanical Engineering 259
- Computer Vision and Pattern Recognition 158
- Computational Mechanics 124
- Biomedical Engineering 119
Countries citing papers authored by Shun Kiyono
This map shows the geographic impact of Shun Kiyono'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 Shun Kiyono with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shun Kiyono more than expected).
Fields of papers citing papers by Shun Kiyono
This network shows the impact of papers produced by Shun Kiyono. 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 Shun Kiyono. The network helps show where Shun Kiyono may publish in the future.
Co-authorship network of co-authors of Shun Kiyono
This figure shows the co-authorship network connecting the top 25 collaborators of Shun Kiyono. A scholar is included among the top collaborators of Shun Kiyono 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 Shun Kiyono. Shun Kiyono is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 4 | |
| 3 | 3 | |
| 4 | 9 | |
| 5 | 24 | |
| 6 | 83 | |
| 7 | 4 | |
| 8 | 7 | |
| 9 | 4 | |
| 10 | Reducing Odd Generation from Neural Headline Generation | 3 |
| 11 | 23 | |
| 12 | Construction of a measurement and control system for a sawyer motor-driven planar motion stage | 1 |
| 13 | 2 | |
| 14 | 6 | |
| 15 | 3 | |
| 16 | 0 | |
| 17 | 7 | |
| 18 | 58 | |
| 19 | 3 | |
| 20 | 12 |
About Shun Kiyono
Shun Kiyono is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 36 papers that have together received 628 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (14 papers), Topic Modeling (13 papers) and Advanced Measurement and Metrology Techniques (12 papers). The work is most often cited by research in Artificial Intelligence (263 citations), Computer Vision and Pattern Recognition (158 citations) and Mechanical Engineering (259 citations). Shun Kiyono has collaborated with scholars based in Japan and United States. Frequent co-authors include Jun Suzuki, Wei Gao, Kentaro Inui, Peisen S. Huang, Masato Mita, Sho Takase, Tomoya Mizumoto, Masahiro Kaneko, Yuki Shimizu and Eiichi Satoh. Their work appears in journals such as Review of Scientific Instruments, CIRP Annals and Sensors and Actuators A Physical.
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.