Soshi Iba
- Control and Systems Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Human-Computer Interaction top 5%
- Artificial Intelligence
- Biomedical Engineering
- Co-authors
- Christiaan J. J. ParedisNawid JamaliP.K. KhoslaDaniel SeitaPradeep K. KhoslaKen GoldbergAshwin BalakrishnaRyan Hoque
- Topics
- Robot Manipulation and Learning (17 papers)Soft Robotics and Applications (4 papers)Tactile and Sensory Interactions (4 papers)
- Cited by
- Human-Computer InteractionControl and Systems EngineeringComputer Vision and Pattern Recognition
- Journals
- The International Journal of Robotics ResearchAutonomous RobotsIEEE Robotics and Automation Letters
- Partner nations
- United StatesJapanGermany
In The Last Decade
Soshi Iba
23 papers receiving 398 citations
Peers
Comparison fields: 5 of 47
- Control and Systems Engineering 234
- Computer Vision and Pattern Recognition 165
- Human-Computer Interaction 83
- Artificial Intelligence 80
- Biomedical Engineering 79
Countries citing papers authored by Soshi Iba
This map shows the geographic impact of Soshi Iba'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 Soshi Iba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soshi Iba more than expected).
Fields of papers citing papers by Soshi Iba
This network shows the impact of papers produced by Soshi Iba. 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 Soshi Iba. The network helps show where Soshi Iba may publish in the future.
Co-authorship network of co-authors of Soshi Iba
This figure shows the co-authorship network connecting the top 25 collaborators of Soshi Iba. A scholar is included among the top collaborators of Soshi Iba 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 Soshi Iba. Soshi Iba 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 | 1 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 8 | |
| 7 | 2 | |
| 8 | 38 | |
| 9 | 35 | |
| 10 | 72 | |
| 11 | 5 | |
| 12 | 40 | |
| 13 | Deep Imitation Learning of Sequential Fabric Smoothing Policies | 9 |
| 14 | Robot Bed-Making: Deep Transfer Learning Using Depth Sensing of Deformable Fabric. | 10 |
| 15 | 2 | |
| 16 | 43 | |
| 17 | 18 | |
| 18 | 18 | |
| 19 | 15 | |
| 20 | 1 |
About Soshi Iba
Soshi Iba is a scholar working on Human-Computer Interaction, Control and Systems Engineering and Industrial and Manufacturing Engineering, having authored 24 papers that have together received 424 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (17 papers), Soft Robotics and Applications (4 papers) and Tactile and Sensory Interactions (4 papers). The work is most often cited by research in Human-Computer Interaction (83 citations), Control and Systems Engineering (234 citations) and Computer Vision and Pattern Recognition (165 citations). Soshi Iba has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include Christiaan J. J. Paredis, Nawid Jamali, P.K. Khosla, Daniel Seita, Pradeep K. Khosla, Ken Goldberg, Ashwin Balakrishna, Ryan Hoque, Katsu Yamane and Peter Trautman. Their work appears in journals such as The International Journal of Robotics Research, Autonomous Robots and IEEE Robotics and Automation Letters.
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.