Tetsuya Sakurai
- Computational Theory and Mathematics top 0.5%
- Atomic and Molecular Physics, and Optics top 5%
- Numerical Analysis top 2%
- Molecular Biology
- Artificial Intelligence top 5%
- Co-authors
- Xiucai YeHiroshi SugiuraHiroto TadanoTsutomu IkegamiAkira ImakuraYasunori FutamuraLeyi WeiLesong Wei
- Topics
- Matrix Theory and Algorithms (52 papers)Electromagnetic Scattering and Analysis (25 papers)Face and Expression Recognition (19 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsScientific Reports
In The Last Decade
Tetsuya Sakurai
142 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 138
- Computational Theory and Mathematics 833
- Atomic and Molecular Physics, and Optics 526
- Numerical Analysis 421
- Molecular Biology 403
- Artificial Intelligence 261
Countries citing papers authored by Tetsuya Sakurai
This map shows the geographic impact of Tetsuya Sakurai'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 Tetsuya Sakurai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tetsuya Sakurai more than expected).
Fields of papers citing papers by Tetsuya Sakurai
This network shows the impact of papers produced by Tetsuya Sakurai. 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 Tetsuya Sakurai. The network helps show where Tetsuya Sakurai may publish in the future.
Co-authorship network of co-authors of Tetsuya Sakurai
This figure shows the co-authorship network connecting the top 25 collaborators of Tetsuya Sakurai. A scholar is included among the top collaborators of Tetsuya Sakurai 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 Tetsuya Sakurai. Tetsuya Sakurai 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 | 0 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 26 | |
| 7 | 0 | |
| 8 | 6 | |
| 9 | 0 | |
| 10 | 4 | |
| 11 | 3 | |
| 12 | 0 | |
| 13 | 10 | |
| 14 | 37 | |
| 15 | 111 | |
| 16 | 7 | |
| 17 | Spectral clustering and discriminant analysis for unsupervised feature selection. | 1 |
| 18 | 18 | |
| 19 | 3 | |
| 20 | A method for locating clusters of zeros of analytic functions | 2 |
About Tetsuya Sakurai
Tetsuya Sakurai is a scholar working on Numerical Analysis, Computational Mathematics and Computational Theory and Mathematics, having authored 157 papers that have together received 1.9k indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (52 papers), Electromagnetic Scattering and Analysis (25 papers) and Face and Expression Recognition (19 papers). The work is most often cited by research in Numerical Analysis (421 citations), Computational Mathematics (43 citations) and Computational Theory and Mathematics (833 citations). Tetsuya Sakurai has collaborated with scholars based in Japan, China and Belgium. Frequent co-authors include Xiucai Ye, Hiroshi Sugiura, Hiroto Tadano, Tsutomu Ikegami, Akira Imakura, Yasunori Futamura, Leyi Wei, Lesong Wei, Umpei Nagashima and Kinji Kimura. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and Scientific Reports.
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.