Xiaofeng Mao
Impact in
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- Advanced Neural Network Applications
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- Reliability and Maintenance Optimization
Papers in
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- Advanced Neural Network Applications 4
- Generative Adversarial Networks and Image Synthesis 3
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- Adversarial Robustness in Machine Learning 9
- Domain Adaptation and Few-Shot Learning 6
- Co-authors
- Yuan HeQian WangRanjie DuanYuefeng ChenHui XueJunbo SonQiang ZhouMutasim Salman
- Journals
- Neurocomputing (2 papers)Journal of Vibration and Control (2 papers)IEEE Transactions on Image Processing (1 paper)IEEE Transactions on Control Systems Technology (1 paper)European Journal of Preventive Cardiology (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Xiaofeng Mao
35 papers receiving 678 citations
Peers
Comparison fields: 5 of 98
- Computer Vision and Pattern Recognition 196
- Safety, Risk, Reliability and Quality 85
- Automotive Engineering 100
- Artificial Intelligence 223
- Software 20
Countries citing papers authored by Xiaofeng Mao
This map shows the geographic impact of Xiaofeng Mao'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 Xiaofeng Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaofeng Mao more than expected).
Fields of papers citing papers by Xiaofeng Mao
This network shows the impact of papers produced by Xiaofeng Mao. 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 Xiaofeng Mao. The network helps show where Xiaofeng Mao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaofeng Mao, 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 | 2024 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 6 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 6 | |
| 9 | 2022 | 6 | |
| 10 | 2022 | 117 | |
| 11 | 2021 | 29 | |
| 12 | 2021 | 16 | |
| 13 | 2021 | 5 | |
| 14 | 2020 | 12 | |
| 15 | 2018 | 34 | |
| 16 | 2013 | 22 | |
| 17 | 2011 | 21 | |
| 18 | Nonlinear Robust Control Design for a High-speed Supercavitating Vehicle | 2010 | 5 |
| 19 | 2008 | 4 | |
| 20 | 2008 | 1 |
About Xiaofeng Mao
Xiaofeng Mao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Hardware and Architecture and Instrumentation, having authored 38 papers that have together received 698 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (9 papers), Domain Adaptation and Few-Shot Learning (6 papers), Electromagnetic Launch and Propulsion Technology (5 papers), Cavitation Phenomena in Pumps (4 papers), Advanced Battery Technologies Research (4 papers), Advanced Neural Network Applications (4 papers), Hydraulic and Pneumatic Systems (4 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (196 citations), Safety, Risk, Reliability and Quality (85 citations), Automotive Engineering (100 citations), Artificial Intelligence (223 citations) and Software (20 citations). Xiaofeng Mao has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yuan He, Qian Wang, Ranjie Duan, Yuefeng Chen, Hui Xue, Junbo Son, Qiang Zhou, Mutasim Salman, Shiyu Zhou and Xiaodan Li. Their work appears in journals such as Neurocomputing, Journal of Vibration and Control, IEEE Transactions on Image Processing, IEEE Transactions on Control Systems Technology and European Journal of Preventive Cardiology.
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.