Bing Chen
- Control and Systems Engineering top 0.02%
- Adaptive Control of Nonlinear Systems 110
- Stability and Control of Uncertain Systems 98
- Iterative Learning Control Systems 24
- Computational Theory and Mathematics top 0.05%
- Adaptive Dynamic Programming Control 41
- Matrix Theory and Algorithms 26
- Computer Networks and Communications top 0.1%
- Neural Networks Stability and Synchronization 85
- Distributed Control Multi-Agent Systems 26
- Statistical and Nonlinear Physics top 0.5%
- Artificial Intelligence top 0.5%
- Neural Networks and Applications 23
Bing Chen
233 papers receiving 12.2k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Control and Systems Engineering 10.5k
- Computational Theory and Mathematics 3.7k
- Computer Networks and Communications 5.0k
- Statistical and Nonlinear Physics 1.1k
- Artificial Intelligence 1.9k
Countries citing papers authored by Bing Chen
This map shows the geographic impact of Bing Chen'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 Bing Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bing Chen more than expected).
Fields of papers citing papers by Bing Chen
This network shows the impact of papers produced by Bing Chen. 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 Bing Chen. The network helps show where Bing Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bing Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2023 | 6 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 6 | |
| 6 | Adaptive Fuzzy Output-Feedback Consensus Tracking Control of Nonlinear Multiagent Systems in Prescribed Performancebreakdown → | 2022 | 118 |
| 7 | 2021 | 10 | |
| 8 | 2021 | 32 | |
| 9 | 2021 | 57 | |
| 10 | 2020 | 15 | |
| 11 | 2020 | 89 | |
| 12 | 2019 | 11 | |
| 13 | 2019 | 33 | |
| 14 | 2019 | 14 | |
| 15 | 2018 | 22 | |
| 16 | 2018 | 33 | |
| 17 | 2018 | 20 | |
| 18 | 2018 | 13 | |
| 19 | 2018 | 61 | |
| 20 | 2017 | 135 |
About Bing Chen
Bing Chen is a scholar working on Control and Systems Engineering, Computational Theory and Mathematics, Computer Networks and Communications, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 250 papers that have together received 12.4k indexed citations. Recurring topics across this work include Adaptive Control of Nonlinear Systems (110 papers), Stability and Control of Uncertain Systems (98 papers), Neural Networks Stability and Synchronization (85 papers), Adaptive Dynamic Programming Control (41 papers), Matrix Theory and Algorithms (26 papers), Distributed Control Multi-Agent Systems (26 papers), Iterative Learning Control Systems (24 papers) and Neural Networks and Applications (23 papers). The work is most often cited by research in Control and Systems Engineering (10.5k citations), Computational Theory and Mathematics (3.7k citations), Computer Networks and Communications (5.0k citations), Statistical and Nonlinear Physics (1.1k citations) and Artificial Intelligence (1.9k citations). Bing Chen has collaborated with scholars based in China, Canada and South Africa. Frequent co-authors include Chong Lin, Xiaoping Liu, Kefu Liu, Fang Wang, Huanqing Wang, Yumei Sun, Qi Zhou, Shaocheng Tong, Hongyi Li and Huaguang Zhang. Their work appears in journals such as Neurocomputing, IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems, Information Sciences and Journal of the Franklin Institute.
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.