Sheng Zhou
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- AI in cancer detection
- Domain Adaptation and Few-Shot Learning
-
- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
Papers in
-
- Advanced Graph Neural Networks 14
- Domain Adaptation and Few-Shot Learning 6
- Topic Modeling 6
- Anomaly Detection Techniques and Applications 3
- Machine Learning and Algorithms 3
- Co-authors
- Jiajun Bu (17 shared papers)Jiawei Chen (11 shared papers)Jingjun Gu (3 shared papers)Xin Shen (1 shared paper)Lei Wu (1 shared paper)Zhe Liu (1 shared paper)Xiangnan He (2 shared papers)Xuezhi Cao (2 shared papers)
- Journals
- Neural Networks (4 papers)ACM Transactions on Information Systems (2 papers)IEEE Transactions on Neural Networks and Learning Systems (2 papers)ACM Transactions on Knowledge Discovery from Data (1 paper)Information Sciences (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Sheng Zhou
28 papers receiving 388 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 235
- Computer Vision and Pattern Recognition 133
- Information Systems 123
- Health Informatics 4
- Radiology, Nuclear Medicine and Imaging 55
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 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 129 | |
| 2 | 2022 | 58 | |
| 3 | 2024 | 24 | |
| 4 | 2024 | 24 | |
| 5 | 2022 | 18 | |
| 6 | 2024 | 15 | |
| 7 | 2022 | 15 | |
| 8 | 2023 | 14 | |
| 9 | 2023 | 14 | |
| 10 | 2024 | 13 | |
| 11 | 2023 | 12 | |
| 12 | 2023 | 11 | |
| 13 | 2023 | 10 | |
| 14 | 2024 | 6 | |
| 15 | 2025 | 6 | |
| 16 | 2023 | 5 | |
| 17 | 2024 | 3 | |
| 18 | 2025 | 3 | |
| 19 | 2025 | 1 | |
| 20 | 2025 | 1 |
About Sheng Zhou
Sheng Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Management Science and Operations Research, having authored 34 papers that have together received 390 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (14 papers), Recommender Systems and Techniques (11 papers), Domain Adaptation and Few-Shot Learning (6 papers), Topic Modeling (6 papers), Complex Network Analysis Techniques (4 papers), Advanced Bandit Algorithms Research (4 papers), Anomaly Detection Techniques and Applications (3 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (235 citations), Computer Vision and Pattern Recognition (133 citations), Information Systems (123 citations), Health Informatics (4 citations) and Radiology, Nuclear Medicine and Imaging (55 citations). Sheng Zhou has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Jiajun Bu, Jiawei Chen, Jingjun Gu, Xin Shen, Lei Wu, Zhe Liu, Xiangnan He, Xuezhi Cao, Zihao Zhao and Fuzheng Zhang. Their work appears in journals such as Neural Networks, ACM Transactions on Information Systems, IEEE Transactions on Neural Networks and Learning Systems, ACM Transactions on Knowledge Discovery from Data and Information Sciences.
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.