Kaifang Wan
- Aerospace Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Control and Systems Engineering top 10%
- Topics
- Reinforcement Learning in Robotics (10 papers)Distributed Control Multi-Agent Systems (9 papers)Robotic Path Planning Algorithms (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionAerospace EngineeringComputer Networks and Communications
- Partner nations
- ChinaRussiaUnited States
In The Last Decade
Kaifang Wan
35 papers receiving 442 citations
Peers
Comparison fields: 5 of 67
- Aerospace Engineering 223
- Computer Vision and Pattern Recognition 206
- Artificial Intelligence 156
- Computer Networks and Communications 114
- Control and Systems Engineering 80
Countries citing papers authored by Kaifang Wan
This map shows the geographic impact of Kaifang Wan'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 Kaifang Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaifang Wan more than expected).
Fields of papers citing papers by Kaifang Wan
This network shows the impact of papers produced by Kaifang Wan. 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 Kaifang Wan. The network helps show where Kaifang Wan may publish in the future.
Co-authorship network of co-authors of Kaifang Wan
This figure shows the co-authorship network connecting the top 25 collaborators of Kaifang Wan. A scholar is included among the top collaborators of Kaifang Wan 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 Kaifang Wan. Kaifang Wan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 12 | |
| 6 | 1 | |
| 7 | 22 | |
| 8 | 1 | |
| 9 | 19 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 32 | |
| 13 | 15 | |
| 14 | 1 | |
| 15 | 34 | |
| 16 | 7 | |
| 17 | 1 | |
| 18 | 8 | |
| 19 | 12 | |
| 20 | Optimal Power Management for Antagonizing Between Radar and Jamming Based on Continuous Game Theory | 1 |
About Kaifang Wan
Kaifang Wan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering, having authored 39 papers that have together received 452 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (10 papers), Distributed Control Multi-Agent Systems (9 papers) and Robotic Path Planning Algorithms (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (206 citations), Aerospace Engineering (223 citations) and Computer Networks and Communications (114 citations). Kaifang Wan has collaborated with scholars based in China, Russia and United States. Frequent co-authors include Zijian Hu, Xiaoguang Gao, Yiwei Zhai, Bo Li, Gaofeng Wu, Xiaoguang Gao, Qianglong Wang, Daqing Chen, Xiaowei Fu and Jinliang Li. Their work appears in journals such as Expert Systems with Applications, Sensors and IEEE Transactions on Vehicular 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.