Jing Yan

2.7k total citations
121 papers, 2.0k citations indexed

About

Jing Yan is a scholar working on Computer Networks and Communications, Ocean Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Jing Yan has authored 121 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Computer Networks and Communications, 62 papers in Ocean Engineering and 32 papers in Electrical and Electronic Engineering. Recurrent topics in Jing Yan's work include Underwater Vehicles and Communication Systems (60 papers), Distributed Control Multi-Agent Systems (56 papers) and Indoor and Outdoor Localization Technologies (25 papers). Jing Yan is often cited by papers focused on Underwater Vehicles and Communication Systems (60 papers), Distributed Control Multi-Agent Systems (56 papers) and Indoor and Outdoor Localization Technologies (25 papers). Jing Yan collaborates with scholars based in China, United States and Canada. Jing Yan's co-authors include Xinping Guan, Xiaoyuan Luo, Xian Yang, Cailian Chen, Changchun Hua, Yiyin Wang, Haiyan Zhao, Yan Wan, Ning Lü and Yuan Meng and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Industrial Electronics and IEEE Access.

In The Last Decade

Jing Yan

116 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jing Yan China 27 934 899 643 636 268 121 2.0k
Jinwhan Kim South Korea 24 1.2k 1.2× 211 0.2× 443 0.7× 276 0.4× 149 0.6× 162 2.0k
Bo Xu China 24 518 0.6× 170 0.2× 581 0.9× 690 1.1× 191 0.7× 116 2.0k
Pan-Mook Lee South Korea 21 1.5k 1.6× 211 0.2× 934 1.5× 143 0.2× 242 0.9× 126 2.1k
Anı́bal Matos Portugal 21 1.1k 1.2× 205 0.2× 189 0.3× 303 0.5× 97 0.4× 137 1.6k
Liam Paull Canada 22 1.3k 1.4× 216 0.2× 378 0.6× 699 1.1× 136 0.5× 64 2.6k
A. J. Healey United States 20 1.6k 1.7× 289 0.3× 1.2k 1.9× 121 0.2× 230 0.9× 98 2.4k
Bong-Huan Jun South Korea 19 1.1k 1.1× 144 0.2× 540 0.8× 102 0.2× 197 0.7× 96 1.5k
Mohd Rizal Arshad Malaysia 15 587 0.6× 159 0.2× 301 0.5× 145 0.2× 119 0.4× 150 1.2k
Shalabh Gupta United States 21 194 0.2× 208 0.2× 423 0.7× 326 0.5× 163 0.6× 82 1.3k
Yu Hu China 22 432 0.5× 596 0.7× 155 0.2× 846 1.3× 165 0.6× 93 2.0k

Countries citing papers authored by Jing Yan

Since Specialization
Citations

This map shows the geographic impact of Jing Yan'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 Jing Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Yan more than expected).

Fields of papers citing papers by Jing Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jing Yan. 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 Jing Yan. The network helps show where Jing Yan may publish in the future.

Co-authorship network of co-authors of Jing Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Yan. A scholar is included among the top collaborators of Jing Yan 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 Jing Yan. Jing Yan 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.
Wen, Yintang, et al.. (2025). Multi-Target Detection in Underwater Sensor Networks Based on Bayesian Deep Learning. IEEE Transactions on Network Science and Engineering. 12(3). 1581–1596. 1 indexed citations
2.
Yan, Jing, et al.. (2025). A Survey on Integration Design of Localization, Communication, and Control for Underwater Acoustic Sensor Networks. IEEE Internet of Things Journal. 12(6). 6300–6324. 12 indexed citations
3.
Zhou, Jianhang, et al.. (2025). Consensus Estimation of Flow Field via Underwater Sensor Networks in Inhomogeneous Medium. IEEE Transactions on Circuits & Systems II Express Briefs. 72(4). 633–637. 1 indexed citations
4.
Yan, Jing, et al.. (2024). Cooperation Detection and Tracking of Underwater Target via Aerial–Surface–Underwater Vehicles. IEEE Transactions on Automatic Control. 70(2). 1068–1083. 4 indexed citations
5.
Yan, Jing, et al.. (2024). Minimum Time Formation Control of AUVs With Smooth Transition in Communication Topology. IEEE Robotics and Automation Letters. 9(10). 8698–8705. 1 indexed citations
6.
Yang, Xian, Jing Yan, Chuanzhi Chen, Changchun Hua, & Xinping Guan. (2024). Adaptive Asymptotic Tracking Control for Underactuated Autonomous Underwater Vehicles With State Constraints. IEEE Transactions on Intelligent Transportation Systems. 25(11). 18485–18500. 2 indexed citations
7.
Yan, Jing, et al.. (2024). Bearing Rigidity-Based Flocking Control of AUVs via Semi-Supervised Incremental Broad Learning. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 7666–7680. 3 indexed citations
8.
Yan, Jing, et al.. (2024). Digital Twin-Driven Formation Control of ROVs: An Integral Reinforcement Learning-Based Solution. IEEE Transactions on Industrial Informatics. 20(12). 14277–14286. 1 indexed citations
9.
Yan, Jing, et al.. (2024). Design of an Embedded System for Integrated Underwater Communication and Detection. IEEE Embedded Systems Letters. 17(2). 83–86. 1 indexed citations
10.
Yan, Jing, et al.. (2024). Teleoperation Control of Autonomous Underwater Vehicle Toward Human on the Loop: Needs, Analyses, and Solutions. IEEE Systems Man and Cybernetics Magazine. 10(3). 2–13. 6 indexed citations
11.
Zhang, Yuyan, et al.. (2023). Cluster-based fusion detection of soft and hard decisions for underwater non-cooperative targets. Signal Processing. 217. 109327–109327. 5 indexed citations
12.
Yan, Jing, et al.. (2023). Binocular Vision-Based Motion Planning of an AUV: A Deep Reinforcement Learning Approach. IEEE Transactions on Intelligent Vehicles. 9(8). 5299–5315. 8 indexed citations
13.
Zhou, Jianhang, Jing Yan, Xian Yang, & Xiaoyuan Luo. (2023). Estimation of Ocean Current Using Dynamic Underwater Acoustic Sensor Network Composed of Multiple AUVs. 57. 1374–1379. 1 indexed citations
14.
15.
Yan, Jing, et al.. (2022). Communication-Efficient and Collision-Free Motion Planning of Underwater Vehicles via Integral Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems. 35(6). 8306–8320. 14 indexed citations
16.
Meng, Yuan, Jing Yan, Xian Yang, & Xiaoyuan Luo. (2020). Privacy Preserving Localization Algorithm for Underwater Sensor Networks. 4481–4486. 2 indexed citations
17.
Wang, Fenfang, Nengwang Chen, Jing Yan, et al.. (2019). Major Processes Shaping Mangroves as Inorganic Nitrogen Sources or Sinks: Insights From a Multidisciplinary Study. Journal of Geophysical Research Biogeosciences. 124(5). 1194–1208. 38 indexed citations
18.
Yan, Jing, Xinping Guan, Xiaoyuan Luo, & Xian Yang. (2012). Consensus and Trajectory Planning with Input Constraints for Multi-agent Systems. Acta Automatica Sinica. 38(7). 1074–1082. 6 indexed citations
19.
Yan, Jing, Xinping Guan, & Xiaoyuan Luo. (2011). Consensus problem for multi-agent systems: A distributed receding horizon approach. Asian Control Conference. 119–124. 1 indexed citations
20.
Yan, Jing. (2010). Formation and obstacle avoidance algorithm for multi-agent systems. Journal of Hunan University of Science & 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.

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