Hang Su
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- Video Surveillance and Tracking Methods 13
- Control and Systems Engineering top 0.5%
- Robot Manipulation and Learning 31
- Human-Computer Interaction top 1%
- Hand Gesture Recognition Systems 12
- Signal Processing top 1%
- Artificial Intelligence top 1%
- Anomaly Detection Techniques and Applications 17
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- Soft Robotics and Applications 29
- Muscle activation and electromyography studies 25
- Prosthetics and Rehabilitation Robotics 22
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- Teleoperation and Haptic Systems 26
Hang Su
211 papers receiving 5.8k citations
Hit Papers
Peers
Comparison fields: 5 of 190
- Computer Vision and Pattern Recognition 1.5k
- Control and Systems Engineering 1.6k
- Human-Computer Interaction 361
- Signal Processing 565
- Artificial Intelligence 1.3k
Countries citing papers authored by Hang Su
This map shows the geographic impact of Hang Su'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 Hang Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hang Su more than expected).
Fields of papers citing papers by Hang Su
This network shows the impact of papers produced by Hang Su. 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 Hang Su. The network helps show where Hang Su may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hang Su, 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 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 3 | |
| 6 | 2024 | 11 | |
| 7 | 2023 | 8 | |
| 8 | 2023 | 13 | |
| 9 | 2023 | 8 | |
| 10 | 2023 | 0 | |
| 11 | 2023 | 9 | |
| 12 | 2023 | 3 | |
| 13 | 2022 | 104 | |
| 14 | 2022 | 21 | |
| 15 | 2022 | 4 | |
| 16 | 2021 | 60 | |
| 17 | 2020 | 42 | |
| 18 | 2020 | 51 | |
| 19 | 2019 | 37 | |
| 20 | 2019 | 16 |
About Hang Su
Hang Su is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering and Signal Processing, having authored 229 papers that have together received 6.0k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (31 papers), Soft Robotics and Applications (29 papers), Teleoperation and Haptic Systems (26 papers), Muscle activation and electromyography studies (25 papers), Prosthetics and Rehabilitation Robotics (22 papers), Anomaly Detection Techniques and Applications (17 papers), Video Surveillance and Tracking Methods (13 papers) and Hand Gesture Recognition Systems (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Control and Systems Engineering (1.6k citations), Human-Computer Interaction (361 citations), Signal Processing (565 citations) and Artificial Intelligence (1.3k citations). Hang Su has collaborated with scholars based in China, Italy and United States. Frequent co-authors include Wen Qi, Giancarlo Ferrigno, Elena De Momi, Yingbai Hu, Zhijun Li, Chenguang Yang, Frank Seide, Dong Yu, Jiehao Li and Andréa Aliverti. Their work appears in journals such as Journal of Biological Chemistry, IEEE/ASME Transactions on Mechatronics, Assembly Automation, Applied Sciences and IEEE Transactions on Systems Man and Cybernetics Systems.
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.