Taichi Nakamura
- Computational Mechanics top 5%
- Statistical and Nonlinear Physics top 2%
- Computer Vision and Pattern Recognition top 10%
- Aerospace Engineering top 10%
- Water Science and Technology top 10%
- Co-authors
- Koji FukagataHiroyuki KonoKai FukamiKazuto HasegawaYuuichi ShimizuHisaho HashimotoKazuo KondoHitoshi Sakano
- Topics
- Model Reduction and Neural Networks (6 papers)Fluid Dynamics and Turbulent Flows (6 papers)Software Engineering Techniques and Practices (5 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Taichi Nakamura
63 papers receiving 944 citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Computational Mechanics 288
- Statistical and Nonlinear Physics 248
- Computer Vision and Pattern Recognition 112
- Aerospace Engineering 100
- Water Science and Technology 99
Countries citing papers authored by Taichi Nakamura
This map shows the geographic impact of Taichi Nakamura'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 Taichi Nakamura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taichi Nakamura more than expected).
Fields of papers citing papers by Taichi Nakamura
This network shows the impact of papers produced by Taichi Nakamura. 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 Taichi Nakamura. The network helps show where Taichi Nakamura may publish in the future.
Co-authorship network of co-authors of Taichi Nakamura
This figure shows the co-authorship network connecting the top 25 collaborators of Taichi Nakamura. A scholar is included among the top collaborators of Taichi Nakamura 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 Taichi Nakamura. Taichi Nakamura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 9 | |
| 4 | 22 | |
| 5 | 6 | |
| 6 | Convolutional neural network and long short-term memory based reduced order surrogate for minimal turbulent channel flowbreakdown → | 144 |
| 7 | 2 | |
| 8 | 138 | |
| 9 | 1 | |
| 10 | 61 | |
| 11 | An analysis of the relation between the behavior of a learner and acquired skill level in role-play training | 4 |
| 12 | 0 | |
| 13 | 17 | |
| 14 | 2 | |
| 15 | TokyoTech's TRECVID2006 Notebook | 1 |
| 16 | A High Speed Distributed Video Transcoder for Multiple Rates and Formats | 1 |
| 17 | A new method to remove metal artifact of 3D-CT image | 1 |
| 18 | A New Stochastic Binary Neural Network Based on Hopfield Model and Its Application | 3 |
| 19 | A study of image recognition system | 2 |
| 20 | 0 |
About Taichi Nakamura
Taichi Nakamura is a scholar working on Computer Science Applications, Signal Processing and Computer Vision and Pattern Recognition, having authored 70 papers that have together received 970 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (6 papers), Fluid Dynamics and Turbulent Flows (6 papers) and Software Engineering Techniques and Practices (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (248 citations), Molecular Medicine (85 citations) and Computational Mechanics (288 citations). Taichi Nakamura has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Koji Fukagata, Hiroyuki Kono, Kai Fukami, Kazuto Hasegawa, Yuuichi Shimizu, Hisaho Hashimoto, Kazuo Kondo, Hitoshi Sakano, Naoki Mukawa and Naoki Okamoto. Their work appears in journals such as Journal of Biological Chemistry, Scientific Reports and Journal of Computational Physics.
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.