Qingfeng Yao
Impact in
-
- Robotic Path Planning Algorithms
- Control and Systems Engineering top 10%
- Control and Dynamics of Mobile Robots
Papers in
-
- Robotic Locomotion and Control 6
- Biosensors and Analytical Detection 4
-
- Advanced biosensing and bioanalysis techniques 4
- Co-authors
- Zhi Liu (3 shared papers)Zeyu Zheng (3 shared papers)Liang Qi (2 shared papers)Xiwang Guo (2 shared papers)Haitao Yuan (1 shared paper)Jingming Gong (4 shared papers)Wensi Yang (1 shared paper)Zheng Cai (2 shared papers)
- Journals
- Analytical Chemistry (3 papers)IEEE Access (2 papers)Robotics and Autonomous Systems (1 paper)Biosensors and Bioelectronics (1 paper)IEEE Robotics and Automation Letters (1 paper)
- Partner nations
- ChinaUnited StatesMontenegro
In The Last Decade
Qingfeng Yao
14 papers receiving 289 citations
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 121
- Control and Systems Engineering 95
- Medical Laboratory Technology 4
- Aerospace Engineering 68
- Automotive Engineering 31
Countries citing papers authored by Qingfeng Yao
This map shows the geographic impact of Qingfeng Yao'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 Qingfeng Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingfeng Yao more than expected).
Fields of papers citing papers by Qingfeng Yao
This network shows the impact of papers produced by Qingfeng Yao. 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 Qingfeng Yao. The network helps show where Qingfeng Yao may publish in the future.
Co-authors
The 25 scholars most cited alongside Qingfeng Yao, 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 | 2020 | 154 | |
| 2 | 2019 | 25 | |
| 3 | 2019 | 24 | |
| 4 | 2024 | 24 | |
| 5 | 2022 | 18 | |
| 6 | 2024 | 17 | |
| 7 | 2021 | 7 | |
| 8 | 2022 | 6 | |
| 9 | 2021 | 5 | |
| 10 | 2023 | 5 | |
| 11 | 2022 | 4 | |
| 12 | An Approach to Extract State Information from Multivariate Time Series | 2020 | 3 |
| 13 | 2019 | 3 | |
| 14 | 2023 | 2 | |
| 15 | 2022 | 0 | |
| 16 | 2025 | 0 |
About Qingfeng Yao
Qingfeng Yao is a scholar working on Biomedical Engineering, Molecular Biology, Control and Systems Engineering, Computer Vision and Pattern Recognition and Mechanical Engineering, having authored 16 papers that have together received 297 indexed citations. Recurring topics across this work include Robotic Locomotion and Control (6 papers), Biosensors and Analytical Detection (4 papers), Advanced biosensing and bioanalysis techniques (4 papers), Robotic Path Planning Algorithms (2 papers), Machine Fault Diagnosis Techniques (2 papers), Advanced Nanomaterials in Catalysis (2 papers), Reinforcement Learning in Robotics (2 papers) and Reliability and Maintenance Optimization (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (121 citations), Control and Systems Engineering (95 citations), Medical Laboratory Technology (4 citations), Aerospace Engineering (68 citations) and Automotive Engineering (31 citations). Qingfeng Yao has collaborated with scholars based in China, United States and Montenegro. Frequent co-authors include Zhi Liu, Zeyu Zheng, Liang Qi, Xiwang Guo, Haitao Yuan, Jingming Gong, Wensi Yang, Zheng Cai, Chengzhong Xu and Kejiang Ye. Their work appears in journals such as Analytical Chemistry, IEEE Access, Robotics and Autonomous Systems, Biosensors and Bioelectronics and IEEE Robotics and Automation Letters.
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.