Zhenshan Bing

1.8k total citations
96 papers, 1.1k citations indexed

About

Zhenshan Bing is a scholar working on Control and Systems Engineering, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhenshan Bing has authored 96 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Control and Systems Engineering, 26 papers in Biomedical Engineering and 22 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhenshan Bing's work include Robot Manipulation and Learning (18 papers), Robotic Locomotion and Control (16 papers) and Advanced Memory and Neural Computing (13 papers). Zhenshan Bing is often cited by papers focused on Robot Manipulation and Learning (18 papers), Robotic Locomotion and Control (16 papers) and Advanced Memory and Neural Computing (13 papers). Zhenshan Bing collaborates with scholars based in Germany, China and United States. Zhenshan Bing's co-authors include Alois Knoll, Kai Huang, Florian Röhrbein, Guang Chen, Long Cheng, Fabrice O. Morin, Xiaojie Su, Walter Stechele, Shu Miao and Pengfei Xia and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Advanced Functional Materials.

In The Last Decade

Zhenshan Bing

79 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhenshan Bing Germany 20 382 263 260 257 255 96 1.1k
Xianlun Tang China 21 511 1.3× 121 0.5× 246 0.9× 306 1.2× 236 0.9× 74 1.3k
Guangshe Zhao China 20 487 1.3× 84 0.3× 198 0.8× 277 1.1× 418 1.6× 52 1.2k
Huapeng Wu Finland 20 220 0.6× 294 1.1× 483 1.9× 136 0.5× 477 1.9× 162 1.5k
Florian Röhrbein Germany 15 399 1.0× 110 0.4× 99 0.4× 374 1.5× 195 0.8× 45 926
Yixin Zhu China 28 492 1.3× 242 0.9× 578 2.2× 282 1.1× 634 2.5× 112 2.3k
Adham Atyabi United States 15 128 0.3× 155 0.6× 220 0.8× 181 0.7× 300 1.2× 45 1.1k
David Howard Australia 16 207 0.5× 788 3.0× 337 1.3× 153 0.6× 173 0.7× 90 1.4k
Arne Roennau Germany 19 221 0.6× 403 1.5× 499 1.9× 134 0.5× 134 0.5× 115 1.3k
Adrian Stoica United States 20 530 1.4× 317 1.2× 96 0.4× 129 0.5× 646 2.5× 169 1.6k

Countries citing papers authored by Zhenshan Bing

Since Specialization
Citations

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

Fields of papers citing papers by Zhenshan Bing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenshan Bing

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenshan Bing. A scholar is included among the top collaborators of Zhenshan Bing 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 Zhenshan Bing. Zhenshan Bing 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.
Wang, Sicheng, et al.. (2025). APT*: Asymptotically Optimal Motion Planning via Adaptively Prolated Elliptical R-Nearest Neighbors. IEEE Robotics and Automation Letters. 10(10). 10242–10249.
2.
Yao, Ling, et al.. (2025). Tree-Based Grafting Approach for Bidirectional Motion Planning With Local Subsets Optimization. IEEE Robotics and Automation Letters. 10(6). 5815–5822. 3 indexed citations
3.
Sun, Zewei, Zhenshan Bing, Chaoqun Wang, et al.. (2025). Motion planning for robotics: A review for sampling-based planners. Repository@Nottingham (University of Nottingham). 5(1). 100207–100207. 9 indexed citations
4.
Bing, Zhenshan, et al.. (2025). Estimated Informed Anytime Search for Sampling-Based Planning via Adaptive Sampler. IEEE Transactions on Automation Science and Engineering. 22. 18580–18593. 1 indexed citations
5.
Wen, Long, et al.. (2025). Meta-Learning-Based Safety-Critical Control in Multi-Obstacles Environments. IEEE Transactions on Automation Science and Engineering. 22. 15299–15313. 2 indexed citations
6.
7.
Li, Yuchen, Luxi Li, Zizhang Wu, et al.. (2024). MiningLLM: Towards Mining 5.0 via Large Language Models in Autonomous Driving and Smart Mining. IEEE Transactions on Intelligent Vehicles. 1–12. 4 indexed citations
8.
Wu, Fan, Lingyun Chen, Samuel J Schneider, et al.. (2024). 1 kHz Behavior Tree for Self-adaptable Tactile Insertion. 16002–16008. 3 indexed citations
9.
Jiang, Tao, et al.. (2024). Adaptive Oscillation-Suppression Control for Distributed Nonholonomic Vehicle Safe Formation With Nested Input Saturation. IEEE Transactions on Automation Science and Engineering. 22. 9140–9152.
10.
Bing, Zhenshan, et al.. (2024). Optimizing Dynamic Balance in a Rat Robot via the Lateral Flexion of a Soft Actuated Spine. mediaTUM (Technical University of Munich). 3442–3448. 1 indexed citations
11.
Su, Xiaojie, et al.. (2024). Efficient Stereo Matching Using Swin Transformer and Multilevel Feature Consistency in Autonomous Mobile Systems. IEEE Transactions on Industrial Informatics. 20(5). 7957–7965.
12.
Bing, Zhenshan, et al.. (2024). Language-Conditioned Imitation Learning With Base Skill Priors Under Unstructured Data. IEEE Robotics and Automation Letters. 9(11). 9805–9812. 4 indexed citations
13.
Wang, Mingyang, Zhenshan Bing, Shuai Wang, et al.. (2023). Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(8). 10157–10165. 8 indexed citations
14.
Bing, Zhenshan, et al.. (2023). Intelligent Transportation Systems Using Roadside Infrastructure: A Literature Survey. IEEE Transactions on Intelligent Transportation Systems. 25(7). 6309–6327. 52 indexed citations
15.
Su, Xiaojie, et al.. (2023). Performance-Driven Safe Bayesian Optimization for Intelligent Tuning of High-Order Cascade Systems. IEEE Transactions on Artificial Intelligence. 5(2). 801–813. 3 indexed citations
16.
Zhang, Lin, et al.. (2023). Task-Based Compliance Control for Bottle Screw Manipulation With a Dual-Arm Robot. IEEE Transactions on Industrial Electronics. 71(2). 1823–1831. 7 indexed citations
17.
Bing, Zhenshan, Rui Li, Xiaojie Su, et al.. (2022). Solving Robotic Manipulation With Sparse Reward Reinforcement Learning Via Graph-Based Diversity and Proximity. IEEE Transactions on Industrial Electronics. 70(3). 2759–2769. 27 indexed citations
18.
Su, Xiaojie, et al.. (2022). Reduced Model-Based Fault Detector and Controller Design for Discrete-Time Switching Fuzzy Systems. IEEE Transactions on Fuzzy Systems. 31(2). 669–681. 8 indexed citations
19.
Bing, Zhenshan, Fabrice O. Morin, Rui Li, et al.. (2021). Complex Robotic Manipulation via Graph-Based Hindsight Goal Generation. IEEE Transactions on Neural Networks and Learning Systems. 33(12). 7863–7876. 26 indexed citations
20.
Chen, Guang, Hu Cao, Jieneng Chen, et al.. (2018). Neuromorphic Vision Based Multivehicle Detection and Tracking for Intelligent Transportation System. Journal of Advanced Transportation. 2018. 1–13. 39 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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