Junbo Ma
Impact in
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Machine Learning in Healthcare
- Domain Adaptation and Few-Shot Learning
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- Face and Expression Recognition
Papers in
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- Advanced Graph Neural Networks 7
- Domain Adaptation and Few-Shot Learning 3
- Machine Learning and ELM 3
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- Graph Theory and Algorithms 3
- Co-authors
- Xiaofeng Zhu (10 shared papers)Yonghua Zhu (3 shared papers)Changan Yuan (1 shared paper)Rongyao Hu (3 shared papers)Guorong Wu (3 shared papers)Ziwen Peng (3 shared papers)Jiangzhang Gan (3 shared papers)Guoqiu Wen (5 shared papers)
- Journals
- Multimedia Tools and Applications (2 papers)Information Sciences (1 paper)IEEE Transactions on Medical Imaging (1 paper)Information Fusion (1 paper)Information Processing & Management (1 paper)
- Partner nations
- ChinaNew ZealandUnited States
In The Last Decade
Junbo Ma
18 papers receiving 327 citations
Peers
Comparison fields: 5 of 63
- Artificial Intelligence 187
- Computer Vision and Pattern Recognition 112
- Computational Mathematics 3
- Neurology 33
- Health Information Management 17
Countries citing papers authored by Junbo Ma
This map shows the geographic impact of Junbo Ma'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 Junbo Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junbo Ma more than expected).
Fields of papers citing papers by Junbo Ma
This network shows the impact of papers produced by Junbo Ma. 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 Junbo Ma. The network helps show where Junbo Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Junbo Ma, 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 | 2021 | 132 | |
| 2 | 2021 | 44 | |
| 3 | 2021 | 40 | |
| 4 | 2023 | 23 | |
| 5 | 2023 | 12 | |
| 6 | 2022 | 11 | |
| 7 | 2018 | 10 | |
| 8 | 2019 | 9 | |
| 9 | 2022 | 9 | |
| 10 | 2018 | 8 | |
| 11 | 2022 | 7 | |
| 12 | 2023 | 6 | |
| 13 | 2023 | 5 | |
| 14 | 2024 | 4 | |
| 15 | 2020 | 4 | |
| 16 | 2024 | 2 | |
| 17 | 2021 | 1 | |
| 18 | 2022 | 1 |
About Junbo Ma
Junbo Ma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Psychiatry and Mental health and Signal Processing, having authored 18 papers that have together received 328 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (7 papers), Functional Brain Connectivity Studies (4 papers), Dementia and Cognitive Impairment Research (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Machine Learning and ELM (3 papers), Graph Theory and Algorithms (3 papers), Brain Tumor Detection and Classification (2 papers) and Music and Audio Processing (2 papers). The work is most often cited by research in Artificial Intelligence (187 citations), Computer Vision and Pattern Recognition (112 citations), Computational Mathematics (3 citations), Neurology (33 citations) and Health Information Management (17 citations). Junbo Ma has collaborated with scholars based in China, New Zealand and United States. Frequent co-authors include Xiaofeng Zhu, Yonghua Zhu, Changan Yuan, Rongyao Hu, Guorong Wu, Ziwen Peng, Jiangzhang Gan, Guoqiu Wen, Ruili Wang and Wanting Ji. Their work appears in journals such as Multimedia Tools and Applications, Information Sciences, IEEE Transactions on Medical Imaging, Information Fusion and Information Processing & Management.
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.