Jun Gao
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Wireless Signal Modulation Classification
- Topic Modeling
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- Ethics in Clinical Research
- Palliative Care and End-of-Life Issues
Papers in ⓘ
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- Topic Modeling 6
- Wireless Signal Modulation Classification 5
- Domain Adaptation and Few-Shot Learning 5
- Advanced Graph Neural Networks 4
- Co-authors
- Dan Cao (1 shared paper)Xianzhen Xu (1 shared paper)Yu Zhou (1 shared paper)Conrad V. Fernandez (6 shared papers)Charles Weijer (5 shared papers)Xiaofei Liu (1 shared paper)Chang Zhou (1 shared paper)Yuqiong Liu (1 shared paper)
- Journals
- Mechanical Systems and Signal Processing (2 papers)Assembly Automation (2 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)IET Radar Sonar & Navigation (2 papers)British Journal of Haematology (1 paper)
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Jun Gao
79 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 147
- Artificial Intelligence 379
- Public Health, Environmental and Occupational Health 224
- Control and Systems Engineering 174
- Statistical and Nonlinear Physics 77
- Computer Vision and Pattern Recognition 127
Countries citing papers authored by Jun Gao
This map shows the geographic impact of Jun Gao'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 Jun Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Gao more than expected).
Fields of papers citing papers by Jun Gao
This network shows the impact of papers produced by Jun Gao. 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 Jun Gao. The network helps show where Jun Gao may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Gao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 156 | |
| 2 | 2017 | 124 | |
| 3 | 2009 | 67 | |
| 4 | 2006 | 59 | |
| 5 | 2010 | 56 | |
| 6 | 2009 | 53 | |
| 7 | 2018 | 46 | |
| 8 | 2018 | 44 | |
| 9 | 2021 | 42 | |
| 10 | 2008 | 41 | |
| 11 | 2012 | 37 | |
| 12 | 2021 | 32 | |
| 13 | 2019 | 27 | |
| 14 | 2017 | 24 | |
| 15 | 2013 | 22 | |
| 16 | 2021 | 22 | |
| 17 | 2022 | 20 | |
| 18 | 2022 | 17 | |
| 19 | 2011 | 17 | |
| 20 | 2012 | 16 |
About Jun Gao
Jun Gao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Public Health, Environmental and Occupational Health and Mechanical Engineering, having authored 85 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Palliative Care and End-of-Life Issues (6 papers), Wireless Signal Modulation Classification (5 papers), Domain Adaptation and Few-Shot Learning (5 papers), Advanced Graph Neural Networks (4 papers), Image Processing Techniques and Applications (4 papers), Fault Detection and Control Systems (3 papers) and Robotic Mechanisms and Dynamics (3 papers). The work is most often cited by research in Artificial Intelligence (379 citations), Public Health, Environmental and Occupational Health (224 citations), Control and Systems Engineering (174 citations), Statistical and Nonlinear Physics (77 citations) and Computer Vision and Pattern Recognition (127 citations). Jun Gao has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Dan Cao, Xianzhen Xu, Yu Zhou, Conrad V. Fernandez, Charles Weijer, Xiaofei Liu, Chang Zhou, Yuqiong Liu, Gaoming Huang and Caron Strahlendorf. Their work appears in journals such as Mechanical Systems and Signal Processing, Assembly Automation, IEEE Transactions on Knowledge and Data Engineering, IET Radar Sonar & Navigation and British Journal of Haematology.
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.