Ryan Hoque
- Control and Systems Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Computational Mechanics
- Biomedical Engineering
- Industrial and Manufacturing Engineering top 10%
- Co-authors
- Ken GoldbergDaniel SeitaAshwin BalakrishnaSoshi IbaNawid JamaliKatsu YamaneBrijen ThananjeyanAjay Kumar Tanwani
- Topics
- Robot Manipulation and Learning (8 papers)Soft Robotics and Applications (3 papers)Robotic Mechanisms and Dynamics (3 papers)
- Journals
- Autonomous Robots2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)
- Partner nations
- United States
In The Last Decade
Ryan Hoque
11 papers receiving 205 citations
Peers
Comparison fields: 5 of 31
- Control and Systems Engineering 133
- Computer Vision and Pattern Recognition 63
- Computational Mechanics 46
- Biomedical Engineering 46
- Industrial and Manufacturing Engineering 39
Countries citing papers authored by Ryan Hoque
This map shows the geographic impact of Ryan Hoque'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 Ryan Hoque with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan Hoque more than expected).
Fields of papers citing papers by Ryan Hoque
This network shows the impact of papers produced by Ryan Hoque. 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 Ryan Hoque. The network helps show where Ryan Hoque may publish in the future.
Co-authorship network of co-authors of Ryan Hoque
This figure shows the co-authorship network connecting the top 25 collaborators of Ryan Hoque. A scholar is included among the top collaborators of Ryan Hoque 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 Ryan Hoque. Ryan Hoque 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 | 15 | |
| 4 | 11 | |
| 5 | 4 | |
| 6 | 35 | |
| 7 | 19 | |
| 8 | 30 | |
| 9 | 72 | |
| 10 | Learning to Smooth and Fold Real Fabric Using Dense Object Descriptors Trained on Synthetic Color Images | 11 |
| 11 | Deep Imitation Learning of Sequential Fabric Smoothing Policies | 9 |
About Ryan Hoque
Ryan Hoque is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 216 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (8 papers), Soft Robotics and Applications (3 papers) and Robotic Mechanisms and Dynamics (3 papers). The work is most often cited by research in Control and Systems Engineering (133 citations), Architecture (7 citations) and Human-Computer Interaction (24 citations). Ryan Hoque has collaborated with scholars based in United States. Frequent co-authors include Ken Goldberg, Daniel Seita, Ashwin Balakrishna, Soshi Iba, Nawid Jamali, Katsu Yamane, Brijen Thananjeyan, Ajay Kumar Tanwani, Minho Hwang and Jeffrey Ichnowski. Their work appears in journals such as Autonomous Robots, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) and 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE).
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.