Yu Kang
- Control and Systems Engineering top 0.2%
- Stability and Control of Uncertain Systems 52
- Adaptive Control of Nonlinear Systems 41
- Advanced Control Systems Optimization 36
- Fault Detection and Control Systems 23
- Computer Networks and Communications top 0.5%
- Distributed Control Multi-Agent Systems 48
- Neural Networks Stability and Synchronization 43
- Geochemistry and Petrology top 2%
- Automotive Engineering top 2%
- Vehicle emissions and performance 26
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- Air Quality Monitoring and Forecasting 27
Yu Kang
318 papers receiving 5.9k citations
Peers
Comparison fields: 5 of 171
- Control and Systems Engineering 2.5k
- Computer Networks and Communications 1.9k
- Geochemistry and Petrology 272
- Automotive Engineering 477
- Computer Vision and Pattern Recognition 545
Countries citing papers authored by Yu Kang
This map shows the geographic impact of Yu Kang'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 Yu Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu Kang more than expected).
Fields of papers citing papers by Yu Kang
This network shows the impact of papers produced by Yu Kang. 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 Yu Kang. The network helps show where Yu Kang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yu Kang, 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 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 3 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 19 | |
| 10 | 2024 | 0 | |
| 11 | 2024 | 5 | |
| 12 | 2023 | 2 | |
| 13 | 2022 | 11 | |
| 14 | 2021 | 1 | |
| 15 | 2021 | 14 | |
| 16 | 2020 | 5 | |
| 17 | Integrating tacrolimus into eutectic oil-based microemulsion for atopic dermatitis: simultaneously enhancing percutaneous delivery and treatment efficacy with relieving side effects | 2019 | 1 |
| 18 | 2019 | 22 | |
| 19 | 2018 | 117 | |
| 20 | 2017 | 204 |
About Yu Kang
Yu Kang is a scholar working on Control and Systems Engineering, Computer Networks and Communications, Automotive Engineering, Environmental Engineering and Artificial Intelligence, having authored 349 papers that have together received 6.1k indexed citations. Recurring topics across this work include Stability and Control of Uncertain Systems (52 papers), Distributed Control Multi-Agent Systems (48 papers), Neural Networks Stability and Synchronization (43 papers), Adaptive Control of Nonlinear Systems (41 papers), Advanced Control Systems Optimization (36 papers), Air Quality Monitoring and Forecasting (27 papers), Vehicle emissions and performance (26 papers) and Fault Detection and Control Systems (23 papers). The work is most often cited by research in Control and Systems Engineering (2.5k citations), Computer Networks and Communications (1.9k citations), Geochemistry and Petrology (272 citations), Automotive Engineering (477 citations) and Computer Vision and Pattern Recognition (545 citations). Yu Kang has collaborated with scholars based in China, Australia and Singapore. Frequent co-authors include Jiahu Qin, Wei Xing Zheng, Zhijun Li, Yun‐Bo Zhao, Yang Cao, Qichao Ma, Guijian Liu, Weiming Fu, Gaosheng Zhang and Wenjun Lv. Their work appears in journals such as IEEE Transactions on Cybernetics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Artificial Intelligence and Neurocomputing.
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.