Takamitsu Matsubara

289 total papers · 2.8k total citations
147 papers, 1.9k citations indexed

About

Takamitsu Matsubara is a scholar working on Control and Systems Engineering, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Takamitsu Matsubara has authored 147 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Control and Systems Engineering, 59 papers in Biomedical Engineering and 58 papers in Artificial Intelligence. Recurrent topics in Takamitsu Matsubara's work include Robot Manipulation and Learning (52 papers), Reinforcement Learning in Robotics (41 papers) and Robotic Locomotion and Control (23 papers). Takamitsu Matsubara is often cited by papers focused on Robot Manipulation and Learning (52 papers), Reinforcement Learning in Robotics (41 papers) and Robotic Locomotion and Control (23 papers). Takamitsu Matsubara collaborates with scholars based in Japan, Australia and Germany. Takamitsu Matsubara's co-authors include Jun Morimoto, Yunduan Cui, Sang-Ho Hyon, Jun Nakanishi, Tomoyuki Noda, Kenji Sugimoto, Gordon Cheng, Gen Endo, Eiji Uchibe and Masashi Hamaya and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Takamitsu Matsubara

136 papers receiving 1.9k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Takamitsu Matsubara 992 885 507 273 273 147 1.9k
Gentiane Venture 981 1.0× 770 0.9× 311 0.6× 405 1.5× 200 0.7× 189 2.3k
Christian Smith 617 0.6× 871 1.0× 441 0.9× 317 1.2× 156 0.6× 91 1.9k
Serena Ivaldi 661 0.7× 648 0.7× 373 0.7× 272 1.0× 255 0.9× 54 1.9k
Andrej Gams 886 0.9× 1.2k 1.3× 367 0.7× 267 1.0× 147 0.5× 73 1.6k
Wen Qi 746 0.8× 594 0.7× 277 0.5× 496 1.8× 239 0.9× 81 2.1k
Yingbai Hu 724 0.7× 843 1.0× 220 0.4× 423 1.5× 189 0.7× 65 1.8k
Dan O. Popa 909 0.9× 813 0.9× 224 0.4× 207 0.8× 258 0.9× 180 2.3k
Majid Nili Ahmadabadi 843 0.8× 643 0.7× 481 0.9× 446 1.6× 304 1.1× 202 2.4k
Freek Stulp 647 0.7× 1.2k 1.3× 565 1.1× 334 1.2× 232 0.8× 102 1.9k
Volkan Patoğlu 801 0.8× 398 0.4× 336 0.7× 182 0.7× 297 1.1× 114 1.6k

Countries citing papers authored by Takamitsu Matsubara

Since Specialization
Citations

This map shows the geographic impact of Takamitsu Matsubara'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 Takamitsu Matsubara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takamitsu Matsubara more than expected).

Fields of papers citing papers by Takamitsu Matsubara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Takamitsu Matsubara. 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 Takamitsu Matsubara. The network helps show where Takamitsu Matsubara may publish in the future.

Co-authorship network of co-authors of Takamitsu Matsubara

This figure shows the co-authorship network connecting the top 25 collaborators of Takamitsu Matsubara. A scholar is included among the top collaborators of Takamitsu Matsubara 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 Takamitsu Matsubara. Takamitsu Matsubara is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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