Takamitsu Matsubara
- Biomedical Engineering top 2%
- Control and Systems Engineering top 1%
- Artificial Intelligence top 2%
- Cognitive Neuroscience top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Jun MorimotoYunduan CuiSang-Ho HyonJun NakanishiTomoyuki NodaKenji SugimotoGordon ChengGen Endo
- Topics
- Robot Manipulation and Learning (54 papers)Reinforcement Learning in Robotics (42 papers)Prosthetics and Rehabilitation Robotics (24 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessIEEE Transactions on Biomedical Engineering
- Partner nations
- JapanAustraliaUnited Kingdom
In The Last Decade
Takamitsu Matsubara
137 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 101
- Biomedical Engineering 1000
- Control and Systems Engineering 896
- Artificial Intelligence 518
- Cognitive Neuroscience 275
- Computer Vision and Pattern Recognition 274
Countries citing papers authored by Takamitsu Matsubara
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 10 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | 4 | |
| 13 | 27 | |
| 14 | 95 | |
| 15 | 12 | |
| 16 | System Identification with Input-Output Manifold Learning | 1 |
| 17 | A Learning Method for Nonlinear Dynamical Motor Primitives from a Variety of Nominal Trajectories : Application to Robot Learning from Demonstration | 1 |
| 18 | Adaptive Step-size Policy Gradients with Average Reward Metric | 4 |
| 19 | 2 | |
| 20 | Learning CPG sensory feedback with policy gradient for biped locomotion for a full-body humanoid | 28 |
About Takamitsu Matsubara
Takamitsu Matsubara is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 150 papers that have together received 2.0k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (54 papers), Reinforcement Learning in Robotics (42 papers) and Prosthetics and Rehabilitation Robotics (24 papers). The work is most often cited by research in Control and Systems Engineering (896 citations), Rehabilitation (167 citations) and Human-Computer Interaction (126 citations). Takamitsu Matsubara has collaborated with scholars based in Japan, Australia and United Kingdom. Frequent 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. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Biomedical Engineering.
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.