Junhao Cai
Impact in
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- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
Papers in
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- Robot Manipulation and Learning 10
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- Advanced Neural Network Applications 4
- Co-authors
- Michael Yu Wang (7 shared papers)Jun Cen (4 shared papers)Ming Liu (3 shared papers)Yun Peng (3 shared papers)Hui Cheng (5 shared papers)Zhanpeng Zhang (3 shared papers)Qifeng Chen (5 shared papers)Hongyu Yu (3 shared papers)
- Journals
- IEEE Robotics and Automation Letters (4 papers)Lecture notes in computer science (1 paper)Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (4 papers)International Conference on 3D Vision (3DV) (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (1 paper)
In The Last Decade
Junhao Cai
15 papers receiving 217 citations
Peers
Comparison fields: 5 of 23
- Computer Vision and Pattern Recognition 97
- Control and Systems Engineering 86
- Automotive Engineering 21
- Artificial Intelligence 66
- Computational Mechanics 39
Countries citing papers authored by Junhao Cai
This map shows the geographic impact of Junhao Cai'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 Junhao Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junhao Cai more than expected).
Fields of papers citing papers by Junhao Cai
This network shows the impact of papers produced by Junhao Cai. 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 Junhao Cai. The network helps show where Junhao Cai may publish in the future.
Co-authors
The 21 scholars most cited alongside Junhao Cai, 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 | 2021 | 67 | |
| 2 | 2019 | 31 | |
| 3 | 2021 | 29 | |
| 4 | 2022 | 24 | |
| 5 | 2022 | 14 | |
| 6 | 2023 | 13 | |
| 7 | 2021 | 11 | |
| 8 | 2024 | 11 | |
| 9 | 2022 | 7 | |
| 10 | 2020 | 6 | |
| 11 | 2024 | 4 | |
| 12 | 2023 | 3 | |
| 13 | 2019 | 1 | |
| 14 | 2022 | 1 | |
| 15 | GIC: Gaussian-Informed Continuum for Physical Property Identification and Simulation | 2024 | 1 |
About Junhao Cai
Junhao Cai is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Computational Mechanics, Artificial Intelligence and Nuclear Energy and Engineering, having authored 15 papers that have together received 223 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (10 papers), Advanced Neural Network Applications (4 papers), Domain Adaptation and Few-Shot Learning (2 papers) and 3D Shape Modeling and Analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (97 citations), Control and Systems Engineering (86 citations), Automotive Engineering (21 citations), Artificial Intelligence (66 citations) and Computational Mechanics (39 citations). Junhao Cai has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Michael Yu Wang, Jun Cen, Ming Liu, Yun Peng, Hui Cheng, Zhanpeng Zhang, Qifeng Chen, Hongyu Yu, Chao Zhao and Shiwei Zhang. Their work appears in journals such as IEEE Robotics and Automation Letters, Lecture notes in computer science, Proceedings - IEEE International Conference on Robotics and Automation/Proceedings, International Conference on 3D Vision (3DV) and Rare & Special e-Zone (The Hong Kong University of Science and Technology).
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.