Mitsuhiro T. Nakao
- Computational Mechanics top 2%
- Computational Theory and Mathematics top 1%
- Statistical and Nonlinear Physics top 2%
- Numerical Analysis top 5%
- Mechanics of Materials top 10%
- Co-authors
- Yoshitaka WatanabeNobito YamamotoKouji HashimotoTakehiko KinoshitaMichael PlumTakuma KimuraNorifumi YamamotoC. S. Ryoo
- Topics
- Advanced Numerical Methods in Computational Mathematics (47 papers)Numerical Methods and Algorithms (33 papers)Model Reduction and Neural Networks (28 papers)
- Journals
- Mathematics of ComputationSIAM Journal on Numerical AnalysisJournal of Mathematical Analysis and Applications
- Partner nations
- JapanGermanySouth Korea
In The Last Decade
Mitsuhiro T. Nakao
82 papers receiving 813 citations
Peers
Comparison fields: 5 of 55
- Computational Mechanics 561
- Computational Theory and Mathematics 496
- Statistical and Nonlinear Physics 336
- Numerical Analysis 211
- Mechanics of Materials 121
Countries citing papers authored by Mitsuhiro T. Nakao
This map shows the geographic impact of Mitsuhiro T. Nakao'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 Mitsuhiro T. Nakao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mitsuhiro T. Nakao more than expected).
Fields of papers citing papers by Mitsuhiro T. Nakao
This network shows the impact of papers produced by Mitsuhiro T. Nakao. 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 Mitsuhiro T. Nakao. The network helps show where Mitsuhiro T. Nakao may publish in the future.
Co-authorship network of co-authors of Mitsuhiro T. Nakao
This figure shows the co-authorship network connecting the top 25 collaborators of Mitsuhiro T. Nakao. A scholar is included among the top collaborators of Mitsuhiro T. Nakao 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 Mitsuhiro T. Nakao. Mitsuhiro T. Nakao 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 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | 9 | |
| 12 | 1 | |
| 13 | 13 | |
| 14 | 9 | |
| 15 | 8 | |
| 16 | 3 | |
| 17 | 29 | |
| 18 | 27 | |
| 19 | 15 | |
| 20 | Decay of solutions of some nonlinear parabolic equations in noncylindrical domains | 2 |
About Mitsuhiro T. Nakao
Mitsuhiro T. Nakao is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Computational Mechanics, having authored 91 papers that have together received 851 indexed citations. Recurring topics across this work include Advanced Numerical Methods in Computational Mathematics (47 papers), Numerical Methods and Algorithms (33 papers) and Model Reduction and Neural Networks (28 papers). The work is most often cited by research in Numerical Analysis (211 citations), Computational Theory and Mathematics (496 citations) and Statistical and Nonlinear Physics (336 citations). Mitsuhiro T. Nakao has collaborated with scholars based in Japan, Germany and South Korea. Frequent co-authors include Yoshitaka Watanabe, Nobito Yamamoto, Kouji Hashimoto, Takehiko Kinoshita, Michael Plum, Takuma Kimura, Norifumi Yamamoto, C. S. Ryoo, Takaaki Nishida and Toshiharu KAGAWA. Their work appears in journals such as Mathematics of Computation, SIAM Journal on Numerical Analysis and Journal of Mathematical Analysis and 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.