Takayuki Osa
- Control and Systems Engineering top 5%
- Biomedical Engineering top 10%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Surgery
- Co-authors
- Mamoru MitsuishiNaohiko SugitaGerhard NeumannJan PetersJoni PajarinenPieter AbbeelJ. Andrew BagnellAlois Knoll
- Topics
- Robot Manipulation and Learning (12 papers)Soft Robotics and Applications (11 papers)Reinforcement Learning in Robotics (9 papers)
- Cited by
- Control and Systems EngineeringComputer Vision and Pattern RecognitionArtificial Intelligence
- Partner nations
- JapanGermanyUnited Kingdom
In The Last Decade
Takayuki Osa
32 papers receiving 912 citations
Peers
Comparison fields: 5 of 99
- Control and Systems Engineering 370
- Biomedical Engineering 324
- Artificial Intelligence 288
- Computer Vision and Pattern Recognition 231
- Surgery 186
Countries citing papers authored by Takayuki Osa
This map shows the geographic impact of Takayuki Osa'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 Takayuki Osa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takayuki Osa more than expected).
Fields of papers citing papers by Takayuki Osa
This network shows the impact of papers produced by Takayuki Osa. 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 Takayuki Osa. The network helps show where Takayuki Osa may publish in the future.
Co-authorship network of co-authors of Takayuki Osa
This figure shows the co-authorship network connecting the top 25 collaborators of Takayuki Osa. A scholar is included among the top collaborators of Takayuki Osa 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 Takayuki Osa. Takayuki Osa 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 | 0 | |
| 3 | 0 | |
| 4 | 11 | |
| 5 | 15 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization. | 5 |
| 9 | 228 | |
| 10 | 174 | |
| 11 | 16 | |
| 12 | 2 | |
| 13 | 67 | |
| 14 | 34 | |
| 15 | 34 | |
| 16 | 9 | |
| 17 | 50 | |
| 18 | 9 | |
| 19 | 58 | |
| 20 | 1 |
About Takayuki Osa
Takayuki Osa is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 34 papers that have together received 944 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (12 papers), Soft Robotics and Applications (11 papers) and Reinforcement Learning in Robotics (9 papers). The work is most often cited by research in Control and Systems Engineering (370 citations), Computer Vision and Pattern Recognition (231 citations) and Artificial Intelligence (288 citations). Takayuki Osa has collaborated with scholars based in Japan, Germany and United Kingdom. Frequent co-authors include Mamoru Mitsuishi, Naohiko Sugita, Gerhard Neumann, Jan Peters, Joni Pajarinen, Pieter Abbeel, J. Andrew Bagnell, Alois Knoll, C. Staub and Robert Bauernschmitt. Their work appears in journals such as Scientific Reports, IEEE Access and The International Journal of Robotics Research.
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.