Kaifang Wan

665 total citations
39 papers, 452 citations indexed

About

Kaifang Wan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Aerospace Engineering. According to data from OpenAlex, Kaifang Wan has authored 39 papers receiving a total of 452 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 15 papers in Aerospace Engineering. Recurrent topics in Kaifang Wan's work include Reinforcement Learning in Robotics (10 papers), Distributed Control Multi-Agent Systems (9 papers) and Robotic Path Planning Algorithms (9 papers). Kaifang Wan is often cited by papers focused on Reinforcement Learning in Robotics (10 papers), Distributed Control Multi-Agent Systems (9 papers) and Robotic Path Planning Algorithms (9 papers). Kaifang Wan collaborates with scholars based in China, Russia and United States. Kaifang Wan's co-authors include Zijian Hu, Xiaoguang Gao, Yiwei Zhai, Bo Li, Gaofeng Wu, Xiaoguang Gao, Qianglong Wang, Daqing Chen, Xiaowei Fu and Jinliang Li and has published in prestigious journals such as Expert Systems with Applications, Sensors and IEEE Transactions on Vehicular Technology.

In The Last Decade

Kaifang Wan

35 papers receiving 442 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kaifang Wan China 13 223 206 156 114 80 39 452
Yifeng Niu China 12 284 1.3× 285 1.4× 93 0.6× 126 1.1× 83 1.0× 81 573
Brett Bethke United States 9 246 1.1× 200 1.0× 112 0.7× 169 1.5× 126 1.6× 13 459
Haiyin Piao China 12 237 1.1× 172 0.8× 111 0.7× 51 0.4× 48 0.6× 40 466
Joshua Redding United States 11 366 1.6× 277 1.3× 134 0.9× 107 0.9× 95 1.2× 27 568
Alessandro Renzaglia France 12 176 0.8× 226 1.1× 57 0.4× 195 1.7× 77 1.0× 31 441
Leonard Bauersfeld Switzerland 10 259 1.2× 233 1.1× 135 0.9× 62 0.5× 208 2.6× 18 648
James A. Preiss United States 6 265 1.2× 348 1.7× 97 0.6× 235 2.1× 137 1.7× 9 546
Qinan Luo China 9 247 1.1× 176 0.9× 95 0.6× 207 1.8× 112 1.4× 15 469
Marcos R. O. A. Máximo Brazil 11 118 0.5× 114 0.6× 185 1.2× 72 0.6× 121 1.5× 73 480
Huaxin Qiu China 13 292 1.3× 167 0.8× 122 0.8× 314 2.8× 111 1.4× 37 590

Countries citing papers authored by Kaifang Wan

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Qi, Feng, Bo Li, Xiaohan Liu, Xiaoguang Gao, & Kaifang Wan. (2025). Low-high frequency network for spatial–temporal traffic flow forecasting. Engineering Applications of Artificial Intelligence. 158. 111304–111304. 1 indexed citations
2.
Gao, Xiaoguang, et al.. (2024). Feature Analysis Network: An Interpretable Idea in Deep Learning. Cognitive Computation. 16(3). 803–826. 6 indexed citations
3.
Gao, Xiaoguang, et al.. (2024). Relevance Inference Based on Direct Contribution: Counterfactual Explanation to Deep Networks for Intelligent Decision-Making. IEEE Transactions on Intelligent Vehicles. 9(11). 6881–6897. 1 indexed citations
4.
Gao, Xiaoguang, et al.. (2024). Finding community structure in Bayesian networks by heuristic K-standard deviation method. Future Generation Computer Systems. 158. 556–568. 1 indexed citations
5.
Hu, Zijian, et al.. (2023). Asynchronous Curriculum Experience Replay: A Deep Reinforcement Learning Approach for UAV Autonomous Motion Control in Unknown Dynamic Environments. IEEE Transactions on Vehicular Technology. 1–16. 12 indexed citations
6.
Gao, Xiaoguang, et al.. (2023). FENet: A Feature Explanation Network with a Hierarchical Interpretable Architecture for Intelligent Decision-Making. IEEE Transactions on Intelligent Vehicles. 1–19. 1 indexed citations
7.
8.
Feng, Qi, et al.. (2023). An Informer-based Spatio-Temporal network for traffic flow forecasting. 1 indexed citations
9.
Li, Bo, et al.. (2023). Multi-UAV roundup strategy method based on deep reinforcement learning CEL-MADDPG algorithm. Expert Systems with Applications. 245. 123018–123018. 19 indexed citations
10.
Gao, Xiaoguang, et al.. (2022). Generative and discriminative infinite restricted Boltzmann machine training. International Journal of Intelligent Systems. 37(10). 7857–7887. 1 indexed citations
11.
Wan, Kaifang, et al.. (2021). An Improved Approach towards Multi-Agent Pursuit–Evasion Game Decision-Making Using Deep Reinforcement Learning. Entropy. 23(11). 1433–1433. 32 indexed citations
12.
Wan, Kaifang, et al.. (2021). A learning-based flexible autonomous motion control method for UAV in dynamic unknown environments. Journal of Systems Engineering and Electronics. 32(6). 1490–1508. 15 indexed citations
13.
Li, Ye, et al.. (2021). Bayesian network parameter learning algorithm based on improved QMAP. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University. 39(6). 1356–1367.
14.
15.
Wu, Gaofeng, Kaifang Wan, Xiaoguang Gao, & Xiaowei Fu. (2020). Placement of unmanned aerial vehicles as communication relays in two-tiered multi-agent system: Clustering based methods. Journal of Systems Engineering and Electronics. 31(2). 231–242. 7 indexed citations
16.
Wan, Kaifang, et al.. (2020). A RDA-Based Deep Reinforcement Learning Approach for Autonomous Motion Planning of UAV in Dynamic Unknown Environments. Journal of Physics Conference Series. 1487(1). 12006–12006. 1 indexed citations
17.
Liu, Yue‐Feng, et al.. (2019). Intercept Mode Suitable for the Space-Based Kinetic Energy Interceptor. Journal of Shanghai Jiaotong University (Science). 24(5). 671–680. 1 indexed citations
18.
Wan, Kaifang, et al.. (2019). Autonomous Robot Navigation in Dynamic Environment Using Deep Reinforcement Learning. 338–342. 8 indexed citations
19.
Gao, Xiaoguang, et al.. (2018). A Threat Assessment Method for Unmanned Aerial Vehicle Based on Bayesian Networks under the Condition of Small Data Sets. Mathematical Problems in Engineering. 2018. 1–17. 12 indexed citations
20.
Wan, Kaifang, et al.. (2014). Optimal Power Management for Antagonizing Between Radar and Jamming Based on Continuous Game Theory. Transaction of Nanjing University of Aeronautics and Astronautics. 31(4). 386–393. 1 indexed citations

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.

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