Junyu Shi
Impact in
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- IL-33, ST2, and ILC Pathways
- Psoriasis: Treatment and Pathogenesis
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- Water Quality Monitoring Technologies
Papers in
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- Image Enhancement Techniques 2
- Human Pose and Action Recognition 2
- Video Surveillance and Tracking Methods 2
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- Adversarial Robustness in Machine Learning 4
- Privacy-Preserving Technologies in Data 2
- Co-authors
- Xin Sun (2 shared papers)Junyu Dong (2 shared papers)Fang Zheng (6 shared papers)Wei Wan (3 shared papers)Shengshan Hu (4 shared papers)Leo Yu Zhang (4 shared papers)Xinhua Wang (1 shared paper)Huiyu Zhou (1 shared paper)
- Journals
- Frontiers in Immunology (2 papers)Journal of Neuroinflammation (1 paper)Neural Processing Letters (1 paper)Neural Computing and Applications (1 paper)Neuroscience Bulletin (1 paper)
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Junyu Shi
15 papers receiving 316 citations
Peers
Comparison fields: 5 of 87
- Immunology 79
- Water Science and Technology 55
- Neurology 27
- Clinical Biochemistry 18
- Dermatology 21
Countries citing papers authored by Junyu Shi
This map shows the geographic impact of Junyu Shi'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 Junyu Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junyu Shi more than expected).
Fields of papers citing papers by Junyu Shi
This network shows the impact of papers produced by Junyu Shi. 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 Junyu Shi. The network helps show where Junyu Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Junyu Shi, 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 | 2017 | 78 | |
| 2 | 2022 | 54 | |
| 3 | 2020 | 41 | |
| 4 | 2018 | 36 | |
| 5 | 2016 | 31 | |
| 6 | 2018 | 22 | |
| 7 | 2021 | 15 | |
| 8 | 2022 | 15 | |
| 9 | 2024 | 9 | |
| 10 | 2021 | 8 | |
| 11 | 2022 | 5 | |
| 12 | 2023 | 3 | |
| 13 | 2018 | 2 | |
| 14 | 2025 | 1 | |
| 15 | 2024 | 1 | |
| 16 | 2026 | 0 | |
| 17 | 2021 | 0 |
About Junyu Shi
Junyu Shi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Clinical Biochemistry, Immunology and Oceanography, having authored 17 papers that have together received 321 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Advanced Glycation End Products research (4 papers), IL-33, ST2, and ILC Pathways (3 papers), Image Enhancement Techniques (2 papers), Human Pose and Action Recognition (2 papers), Privacy-Preserving Technologies in Data (2 papers), Video Surveillance and Tracking Methods (2 papers) and Underwater Acoustics Research (2 papers). The work is most often cited by research in Immunology (79 citations), Water Science and Technology (55 citations), Neurology (27 citations), Clinical Biochemistry (18 citations) and Dermatology (21 citations). Junyu Shi has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Xin Sun, Junyu Dong, Fang Zheng, Wei Wan, Shengshan Hu, Leo Yu Zhang, Xinhua Wang, Huiyu Zhou, Lipeng Liu and Claudia Plant. Their work appears in journals such as Frontiers in Immunology, Journal of Neuroinflammation, Neural Processing Letters, Neural Computing and Applications and Neuroscience Bulletin.
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.