Kunihiko Taira
- Computational Mechanics top 0.1%
- Aerospace Engineering top 0.2%
- Statistical and Nonlinear Physics top 0.2%
- Environmental Engineering top 2%
- Mechanical Engineering top 5%
- Co-authors
- Tim ColoniusKai FukamiKoji FukagataSteven L. BruntonScott T. M. DawsonC. YehLawrence UkeileyVassilios Theofilis
- Topics
- Fluid Dynamics and Turbulent Flows (96 papers)Fluid Dynamics and Vibration Analysis (55 papers)Model Reduction and Neural Networks (36 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaPLoS ONE
- Partner nations
- United StatesJapanUnited Kingdom
In The Last Decade
Kunihiko Taira
135 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Computational Mechanics 4.2k
- Aerospace Engineering 2.4k
- Statistical and Nonlinear Physics 1.8k
- Environmental Engineering 485
- Mechanical Engineering 375
Countries citing papers authored by Kunihiko Taira
This map shows the geographic impact of Kunihiko Taira'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 Kunihiko Taira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kunihiko Taira more than expected).
Fields of papers citing papers by Kunihiko Taira
This network shows the impact of papers produced by Kunihiko Taira. 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 Kunihiko Taira. The network helps show where Kunihiko Taira may publish in the future.
Co-authorship network of co-authors of Kunihiko Taira
This figure shows the co-authorship network connecting the top 25 collaborators of Kunihiko Taira. A scholar is included among the top collaborators of Kunihiko Taira 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 Kunihiko Taira. Kunihiko Taira 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 | 15 | |
| 3 | 13 | |
| 4 | 7 | |
| 5 | 13 | |
| 6 | 6 | |
| 7 | 23 | |
| 8 | 5 | |
| 9 | 7 | |
| 10 | 3 | |
| 11 | Super-resolution analysis via machine learning: a survey for fluid flowsbreakdown → | 94 |
| 12 | 17 | |
| 13 | 93 | |
| 14 | 49 | |
| 15 | Probabilistic neural networks for fluid flow model-order reduction and data recovery | 2 |
| 16 | Super-resolution reconstruction of turbulent flows with machine learningbreakdown → | 483 |
| 17 | Dynamic mode analysis and control of vortical flows in pump sumps | 2 |
| 18 | 27 | |
| 19 | The Role of Vorticity Injection in Separation Control | 1 |
| 20 | 0 |
About Kunihiko Taira
Kunihiko Taira is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Aerospace Engineering, having authored 138 papers that have together received 5.4k indexed citations. Recurring topics across this work include Fluid Dynamics and Turbulent Flows (96 papers), Fluid Dynamics and Vibration Analysis (55 papers) and Model Reduction and Neural Networks (36 papers). The work is most often cited by research in Computational Mechanics (4.2k citations), Statistical and Nonlinear Physics (1.8k citations) and Aerospace Engineering (2.4k citations). Kunihiko Taira has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Tim Colonius, Kai Fukami, Koji Fukagata, Steven L. Brunton, Scott T. M. Dawson, C. Yeh, Lawrence Ukeiley, Vassilios Theofilis, Clarence W. Rowley and Beverley McKeon. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.
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.