Yasuo Kawaguchi
- Cellular and Molecular Neuroscience top 0.05%
- Neuroscience and Neuropharmacology Research 67
- Neuroscience and Neural Engineering 22
- Cognitive Neuroscience top 0.1%
- Neural dynamics and brain function 50
- Developmental Neuroscience top 0.5%
- Fluid Flow and Transfer Processes top 0.5%
- Rheology and Fluid Dynamics Studies 86
- Neurology top 0.5%
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- Fluid Dynamics and Turbulent Flows 108
- Fluid Dynamics and Vibration Analysis 49
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- Heat Transfer Mechanisms 32
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- Particle Dynamics in Fluid Flows 18
Yasuo Kawaguchi
289 papers receiving 14.7k citations
Hit Papers
Peers
Comparison fields: 5 of 171
- Cellular and Molecular Neuroscience 9.9k
- Cognitive Neuroscience 6.5k
- Developmental Neuroscience 925
- Fluid Flow and Transfer Processes 1.2k
- Neurology 1.5k
Countries citing papers authored by Yasuo Kawaguchi
This map shows the geographic impact of Yasuo Kawaguchi'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 Yasuo Kawaguchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yasuo Kawaguchi more than expected).
Fields of papers citing papers by Yasuo Kawaguchi
This network shows the impact of papers produced by Yasuo Kawaguchi. 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 Yasuo Kawaguchi. The network helps show where Yasuo Kawaguchi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yasuo Kawaguchi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 13 | |
| 5 | 2020 | 5 | |
| 6 | 2018 | 4 | |
| 7 | 2018 | 62 | |
| 8 | 2018 | 3 | |
| 9 | 2016 | 8 | |
| 10 | 2016 | 10 | |
| 11 | 2016 | 4 | |
| 12 | 2013 | 39 | |
| 13 | 2012 | 56 | |
| 14 | 2012 | 37 | |
| 15 | 2011 | 104 | |
| 16 | 2010 | 34 | |
| 17 | 2010 | 143 | |
| 18 | Experimental study of surfactant drag-reducing flow in 2-D channel at subzero temperature | 2006 | 1 |
| 19 | TED-AJ03-134 INVESTIGATION ON HEAT TRANSFER CHARACTERISTICS OF DRAG-REDUCING FLOW WITH SURFACTANT ADDITIVE BY SIMULTANEOUS MEASUREMENTS OF TEMPERATURE AND VELOCITYFLUCTUATIONS IN THERMAL BOUNDARY LAYER | 2003 | 3 |
| 20 | Active control of turbulent drag reduction in surfactant solutions by wall heating | 1996 | 11 |
About Yasuo Kawaguchi
Yasuo Kawaguchi is a scholar working on Fluid Flow and Transfer Processes, Computational Mechanics and Cellular and Molecular Neuroscience, having authored 298 papers that have together received 14.9k indexed citations. Recurring topics across this work include Fluid Dynamics and Turbulent Flows (108 papers), Rheology and Fluid Dynamics Studies (86 papers), Neuroscience and Neuropharmacology Research (67 papers), Neural dynamics and brain function (50 papers), Fluid Dynamics and Vibration Analysis (49 papers), Heat Transfer Mechanisms (32 papers), Neuroscience and Neural Engineering (22 papers) and Particle Dynamics in Fluid Flows (18 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (9.9k citations), Cognitive Neuroscience (6.5k citations) and Developmental Neuroscience (925 citations). Yasuo Kawaguchi has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Yoshiyuki Kubota, Charles J. Wilson, Bo Yu, P.C. Emson, Sarah J. Augood, Piers C. Emson, Kiyoshi Hama, Mieko Morishima, Fuyuki Karube and Takeshi Otsuka. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Neuron.
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.