Sheng Zhou
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- AI in cancer detection
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
Papers in
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- Advanced Graph Neural Networks 13
- Domain Adaptation and Few-Shot Learning 6
- Topic Modeling 6
- Machine Learning and Algorithms 3
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- Multimodal Machine Learning Applications 3
- Co-authors
- Jiajun Bu (15 shared papers)Jiawei Chen (11 shared papers)Lei Wu (1 shared paper)Xin Shen (1 shared paper)Zhe Liu (1 shared paper)Xiangnan He (2 shared papers)Xuezhi Cao (2 shared papers)Fuzheng Zhang (1 shared paper)
- Journals
- Neural Networks (4 papers)ACM Transactions on Information Systems (2 papers)Information Sciences (1 paper)IEEE Transactions on Mobile Computing (1 paper)Knowledge-Based Systems (1 paper)
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Sheng Zhou
22 papers receiving 340 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 216
- Computer Vision and Pattern Recognition 125
- Information Systems 108
- Health Informatics 4
- Management Science and Operations Research 31
Countries citing papers authored by Sheng Zhou
This map shows the geographic impact of Sheng 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 Sheng Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheng Zhou more than expected).
Fields of papers citing papers by Sheng Zhou
This network shows the impact of papers produced by Sheng 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 Sheng Zhou. The network helps show where Sheng Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Sheng 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
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 121 | |
| 2 | 2022 | 52 | |
| 3 | 2024 | 22 | |
| 4 | 2022 | 18 | |
| 5 | 2024 | 17 | |
| 6 | 2022 | 15 | |
| 7 | 2023 | 13 | |
| 8 | 2024 | 12 | |
| 9 | 2023 | 12 | |
| 10 | 2024 | 11 | |
| 11 | 2023 | 11 | |
| 12 | 2023 | 9 | |
| 13 | 2023 | 8 | |
| 14 | 2023 | 5 | |
| 15 | 2024 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2025 | 3 | |
| 18 | 2025 | 2 | |
| 19 | 2024 | 1 | |
| 20 | 2025 | 1 |
About Sheng Zhou
Sheng Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Management Science and Operations Research and Statistical and Nonlinear Physics, having authored 30 papers that have together received 342 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (13 papers), Recommender Systems and Techniques (11 papers), Domain Adaptation and Few-Shot Learning (6 papers), Topic Modeling (6 papers), Advanced Bandit Algorithms Research (4 papers), Multimodal Machine Learning Applications (3 papers), Machine Learning and Algorithms (3 papers) and Complex Network Analysis Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (216 citations), Computer Vision and Pattern Recognition (125 citations), Information Systems (108 citations), Health Informatics (4 citations) and Management Science and Operations Research (31 citations). Sheng Zhou has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Jiajun Bu, Jiawei Chen, Lei Wu, Xin Shen, Zhe Liu, Xiangnan He, Xuezhi Cao, Fuzheng Zhang, Wei Wu and Ning Ma. Their work appears in journals such as Neural Networks, ACM Transactions on Information Systems, Information Sciences, IEEE Transactions on Mobile Computing and Knowledge-Based Systems.
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.