Takeshi Sakaguchi
- Control and Systems Engineering top 2%
- Biomedical Engineering top 10%
- Automotive Engineering top 5%
- Computer Vision and Pattern Recognition top 10%
- Molecular Biology
- Co-authors
- Atsuya UnoSadayuki TsugawaFumio KanehiroKenji KanekoMitsuharu MorisawaShuuji KajitaKazuhito YokoiShin’ichiro Nakaoka
- Topics
- Robotic Locomotion and Control (23 papers)Robotics and Automated Systems (14 papers)Robot Manipulation and Learning (13 papers)
- Partner nations
- JapanUnited StatesFrance
In The Last Decade
Takeshi Sakaguchi
55 papers receiving 872 citations
Peers
Comparison fields: 5 of 109
- Control and Systems Engineering 477
- Biomedical Engineering 414
- Automotive Engineering 135
- Computer Vision and Pattern Recognition 135
- Molecular Biology 101
Countries citing papers authored by Takeshi Sakaguchi
This map shows the geographic impact of Takeshi Sakaguchi'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 Takeshi Sakaguchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takeshi Sakaguchi more than expected).
Fields of papers citing papers by Takeshi Sakaguchi
This network shows the impact of papers produced by Takeshi Sakaguchi. 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 Takeshi Sakaguchi. The network helps show where Takeshi Sakaguchi may publish in the future.
Co-authorship network of co-authors of Takeshi Sakaguchi
This figure shows the co-authorship network connecting the top 25 collaborators of Takeshi Sakaguchi. A scholar is included among the top collaborators of Takeshi Sakaguchi 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 Takeshi Sakaguchi. Takeshi Sakaguchi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 8 | |
| 3 | 12 | |
| 4 | 66 | |
| 5 | 10 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | Architectures and models for humanoid robots in collaborative working environments | 1 |
| 12 | 5 | |
| 13 | 9 | |
| 14 | 8 | |
| 15 | 10 | |
| 16 | 5 | |
| 17 | 1 | |
| 18 | 37 | |
| 19 | 22 | |
| 20 | 8 |
About Takeshi Sakaguchi
Takeshi Sakaguchi is a scholar working on Control and Systems Engineering, Biomedical Engineering and Nephrology, having authored 60 papers that have together received 914 indexed citations. Recurring topics across this work include Robotic Locomotion and Control (23 papers), Robotics and Automated Systems (14 papers) and Robot Manipulation and Learning (13 papers). The work is most often cited by research in Control and Systems Engineering (477 citations), Transportation (78 citations) and Automotive Engineering (135 citations). Takeshi Sakaguchi has collaborated with scholars based in Japan, United States and France. Frequent co-authors include Atsuya Uno, Sadayuki Tsugawa, Fumio Kanehiro, Kenji Kaneko, Mitsuharu Morisawa, Shuuji Kajita, Kazuhito Yokoi, Shin’ichiro Nakaoka, Rafael Cisneros and Hiroshi Kaminaga. Their work appears in journals such as Nucleic Acids Research, Journal of Bacteriology and Kidney International.
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.