Kousuke Kuto
Impact in
- Modeling and Simulation top 0.5%
- Mathematical Biology Tumor Growth
- COVID-19 epidemiological studies
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- Mathematical and Theoretical Epidemiology and Ecology Models
Papers in
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- Mathematical and Theoretical Epidemiology and Ecology Models 27
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- Mathematical Biology Tumor Growth 17
- Co-authors
- Yoshio Yamada (6 shared papers)Tohru Tsujikawa (14 shared papers)Hiroshi Matsuzawa (1 shared paper)Rui Peng (1 shared paper)Tatsunari Sakurai (1 shared paper)Koichi Osaki (1 shared paper)Koki Watanabe (1 shared paper)Shoji Yotsutani (5 shared papers)
In The Last Decade
Kousuke Kuto
34 papers receiving 607 citations
Peers
Comparison fields: 5 of 44
- Modeling and Simulation 422
- Public Health, Environmental and Occupational Health 549
- Applied Mathematics 132
- Genetics 348
- Numerical Analysis 35
Countries citing papers authored by Kousuke Kuto
This map shows the geographic impact of Kousuke Kuto'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 Kousuke Kuto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kousuke Kuto more than expected).
Fields of papers citing papers by Kousuke Kuto
This network shows the impact of papers produced by Kousuke Kuto. 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 Kousuke Kuto. The network helps show where Kousuke Kuto may publish in the future.
Co-authors
The 12 scholars most cited alongside Kousuke Kuto, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 123 | |
| 2 | 2017 | 81 | |
| 3 | 2003 | 77 | |
| 4 | 2012 | 61 | |
| 5 | 2006 | 45 | |
| 6 | 2010 | 34 | |
| 7 | 2007 | 32 | |
| 8 | 2014 | 24 | |
| 9 | 2015 | 20 | |
| 10 | 2009 | 19 | |
| 11 | 2012 | 18 | |
| 12 | 2006 | 16 | |
| 13 | 2009 | 12 | |
| 14 | 2007 | 11 | |
| 15 | 2009 | 10 | |
| 16 | 2018 | 8 | |
| 17 | 2017 | 7 | |
| 18 | 2020 | 6 | |
| 19 | 2015 | 6 | |
| 20 | 2016 | 6 |
About Kousuke Kuto
Kousuke Kuto is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation, Applied Mathematics, Genetics and Computer Networks and Communications, having authored 37 papers that have together received 653 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (27 papers), Mathematical Biology Tumor Growth (17 papers), Nonlinear Differential Equations Analysis (10 papers), Evolution and Genetic Dynamics (8 papers), Nonlinear Dynamics and Pattern Formation (7 papers), Nonlinear Partial Differential Equations (6 papers), Advanced Mathematical Modeling in Engineering (6 papers) and Stochastic processes and statistical mechanics (3 papers). The work is most often cited by research in Modeling and Simulation (422 citations), Public Health, Environmental and Occupational Health (549 citations), Applied Mathematics (132 citations), Genetics (348 citations) and Numerical Analysis (35 citations). Kousuke Kuto has collaborated with scholars based in Japan, China and Taiwan. Frequent co-authors include Yoshio Yamada, Tohru Tsujikawa, Hiroshi Matsuzawa, Rui Peng, Tatsunari Sakurai, Koichi Osaki, Koki Watanabe, Shoji Yotsutani, Masaharu Nagayama and Masahiro Adachi. Their work appears in journals such as Journal of Differential Equations, Discrete and Continuous Dynamical Systems, Discrete and Continuous Dynamical Systems - B, SIAM Journal on Mathematical Analysis and Nonlinear Analysis Real World 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.