Junru Zhou
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Text Readability and Simplification
- Speech and dialogue systems
- Advanced Text Analysis Techniques
- Advanced Graph Neural Networks
- Speech Recognition and Synthesis
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- Multimodal Machine Learning Applications
Papers in
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- Natural Language Processing Techniques 8
- Topic Modeling 8
- Text Readability and Simplification 2
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- Multimodal Machine Learning Applications 5
- Co-authors
- Zhuosheng Zhang (2 shared papers)Rui Wang (2 shared papers)Yuwei Wu (1 shared paper)Hai Zhao (1 shared paper)Hai Zhao (7 shared papers)Zuchao Li (4 shared papers)Shuailiang Zhang (1 shared paper)Lifu Zhang (2 shared papers)
In The Last Decade
Junru Zhou
11 papers receiving 187 citations
Peers
Comparison fields: 5 of 31
- Artificial Intelligence 163
- Computer Vision and Pattern Recognition 57
- Analytical Chemistry 5
- Information Systems 11
- Computer Science Applications 2
Countries citing papers authored by Junru Zhou
This map shows the geographic impact of Junru Zhou'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 Junru Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junru Zhou more than expected).
Fields of papers citing papers by Junru Zhou
This network shows the impact of papers produced by Junru Zhou. 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 Junru Zhou. The network helps show where Junru Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Junru Zhou, 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 | 111 | |
| 2 | 2020 | 27 | |
| 3 | 2020 | 17 | |
| 4 | 2019 | 12 | |
| 5 | 2024 | 7 | |
| 6 | 2022 | 3 | |
| 7 | 2024 | 3 | |
| 8 | 2022 | 3 | |
| 9 | 2021 | 3 | |
| 10 | 2025 | 2 | |
| 11 | 2021 | 1 | |
| 12 | 2025 | 0 | |
| 13 | 2022 | 0 | |
| 14 | 2022 | 0 |
About Junru Zhou
Junru Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Ecology, Plant Science and Global and Planetary Change, having authored 14 papers that have together received 189 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Topic Modeling (8 papers), Multimodal Machine Learning Applications (5 papers), Remote Sensing in Agriculture (4 papers), Plant Water Relations and Carbon Dynamics (2 papers), Leaf Properties and Growth Measurement (2 papers), Text Readability and Simplification (2 papers) and Horticultural and Viticultural Research (1 paper). The work is most often cited by research in Artificial Intelligence (163 citations), Computer Vision and Pattern Recognition (57 citations), Analytical Chemistry (5 citations), Information Systems (11 citations) and Computer Science Applications (2 citations). Junru Zhou has collaborated with scholars based in China, Japan and Australia. Frequent co-authors include Zhuosheng Zhang, Rui Wang, Yuwei Wu, Hai Zhao, Hai Zhao, Zuchao Li, Shuailiang Zhang, Lifu Zhang, Shexia He and Changping Huang. Their work appears in journals such as Industrial Crops and Products, Applied Sciences, Agricultural and Forest Meteorology, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and Journal of Artificial Intelligence Research.
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.