Fan Shi
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 5%
- Aerospace Engineering top 5%
- Biomedical Engineering
- Computer Networks and Communications top 10%
- Co-authors
- Masayuki InabaKei OkadaMoju ZhaoTomoki AnzaiXiangyu ChenMasaki MurookaKoji KawasakiShunichi Nozawa
- Topics
- Robotic Path Planning Algorithms (14 papers)Robotics and Sensor-Based Localization (9 papers)Robotic Locomotion and Control (8 papers)
- Cited by
- Computer Vision and Pattern RecognitionControl and Systems EngineeringAerospace Engineering
- Journals
- ACM Transactions on GraphicsThe International Journal of Robotics ResearchIEEE Robotics and Automation Letters
- Partner nations
- JapanSwitzerlandChina
In The Last Decade
Fan Shi
24 papers receiving 415 citations
Peers
Comparison fields: 5 of 38
- Computer Vision and Pattern Recognition 225
- Control and Systems Engineering 212
- Aerospace Engineering 204
- Biomedical Engineering 145
- Computer Networks and Communications 83
Countries citing papers authored by Fan Shi
This map shows the geographic impact of Fan Shi'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 Fan Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fan Shi more than expected).
Fields of papers citing papers by Fan Shi
This network shows the impact of papers produced by Fan Shi. 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 Fan Shi. The network helps show where Fan Shi may publish in the future.
Co-authorship network of co-authors of Fan Shi
This figure shows the co-authorship network connecting the top 25 collaborators of Fan Shi. A scholar is included among the top collaborators of Fan Shi 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 Fan Shi. Fan Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 7 | |
| 6 | 12 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 9 | |
| 11 | 0 | |
| 12 | 8 | |
| 13 | 26 | |
| 14 | 20 | |
| 15 | 13 | |
| 16 | 23 | |
| 17 | 9 | |
| 18 | 25 | |
| 19 | 135 | |
| 20 | 1 |
About Fan Shi
Fan Shi is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Aerospace Engineering, having authored 28 papers that have together received 423 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (14 papers), Robotics and Sensor-Based Localization (9 papers) and Robotic Locomotion and Control (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (225 citations), Control and Systems Engineering (212 citations) and Aerospace Engineering (204 citations). Fan Shi has collaborated with scholars based in Japan, Switzerland and China. Frequent co-authors include Masayuki Inaba, Kei Okada, Moju Zhao, Tomoki Anzai, Xiangyu Chen, Masaki Murooka, Xiangyu Chen, Koji Kawasaki, Shunichi Nozawa and Shintaro Noda. Their work appears in journals such as ACM Transactions on Graphics, The International Journal of Robotics Research 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.