Ryan Hoque
Impact in
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
- Architecture top 10%
Papers in
-
- Robot Manipulation and Learning 8
- Robotic Mechanisms and Dynamics 3
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- Optical measurement and interference techniques 2
- Advanced Vision and Imaging 2
- Human Pose and Action Recognition 2
- Co-authors
- Ken Goldberg (11 shared papers)Ashwin Balakrishna (7 shared papers)Daniel Seita (6 shared papers)Aditya Ganapathi (6 shared papers)Soshi Iba (5 shared papers)Nawid Jamali (5 shared papers)Katsu Yamane (5 shared papers)Brijen Thananjeyan (5 shared papers)
- Journals
- Autonomous Robots (1 paper)2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) (1 paper)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)
- Partner nations
- United States
In The Last Decade
Ryan Hoque
11 papers receiving 217 citations
Peers
Comparison fields: 5 of 31
- Control and Systems Engineering 139
- Architecture 7
- Human-Computer Interaction 25
- Industrial and Manufacturing Engineering 40
- Computer Vision and Pattern Recognition 66
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-authors
The 25 scholars most cited alongside Ryan Hoque, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 73 | |
| 2 | 2021 | 35 | |
| 3 | 2021 | 32 | |
| 4 | 2021 | 21 | |
| 5 | 2023 | 16 | |
| 6 | 2023 | 12 | |
| 7 | 2022 | 11 | |
| 8 | Learning to Smooth and Fold Real Fabric Using Dense Object Descriptors Trained on Synthetic Color Images | 2020 | 11 |
| 9 | Deep Imitation Learning of Sequential Fabric Smoothing Policies | 2019 | 10 |
| 10 | 2022 | 4 | |
| 11 | 2024 | 3 |
About Ryan Hoque
Ryan Hoque is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Biomedical Engineering, Industrial and Manufacturing Engineering and Mechanical Engineering, having authored 11 papers that have together received 228 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (8 papers), Soft Robotics and Applications (3 papers), Robotic Mechanisms and Dynamics (3 papers), Optical measurement and interference techniques (2 papers), Advanced Vision and Imaging (2 papers), Human Pose and Action Recognition (2 papers), Manufacturing Process and Optimization (2 papers) and Modular Robots and Swarm Intelligence (2 papers). The work is most often cited by research in Control and Systems Engineering (139 citations), Architecture (7 citations), Human-Computer Interaction (25 citations), Industrial and Manufacturing Engineering (40 citations) and Computer Vision and Pattern Recognition (66 citations). Ryan Hoque has collaborated with scholars based in United States. Frequent co-authors include Ken Goldberg, Ashwin Balakrishna, Daniel Seita, Aditya Ganapathi, Soshi Iba, Nawid Jamali, Katsu Yamane, Brijen Thananjeyan, Jeffrey Ichnowski and Ajay Kumar Tanwani. Their work appears in journals such as Autonomous Robots, 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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.