Bei Hui
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Information Systems top 5%
- Recommender Systems and Techniques
Papers in
-
- Advanced Graph Neural Networks 15
- Topic Modeling 11
- AI in cancer detection 5
- Text and Document Classification Technologies 3
- Privacy-Preserving Technologies in Data 3
- Co-authors
- Lizong Zhang (7 shared papers)Wen Xiao (1 shared paper)Ling Tian (10 shared papers)Jiajun Qiu (6 shared papers)Guangchun Luo (2 shared papers)Yue Wu (6 shared papers)Xiaobing Zhou (1 shared paper)Chen Jia (1 shared paper)
- Journals
- Expert Systems with Applications (2 papers)Applied Intelligence (2 papers)IEEE Internet of Things Journal (2 papers)Tsinghua Science & Technology (2 papers)Computer Modeling in Engineering & Sciences (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Bei Hui
37 papers receiving 387 citations
Peers
Comparison fields: 5 of 93
- Artificial Intelligence 205
- Information Systems 107
- Computer Vision and Pattern Recognition 87
- Complementary and alternative medicine 34
- Statistical and Nonlinear Physics 41
Countries citing papers authored by Bei Hui
This map shows the geographic impact of Bei Hui'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 Bei Hui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bei Hui more than expected).
Fields of papers citing papers by Bei Hui
This network shows the impact of papers produced by Bei Hui. 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 Bei Hui. The network helps show where Bei Hui may publish in the future.
Co-authors
The 25 scholars most cited alongside Bei Hui, 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 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 100 | |
| 2 | 2003 | 37 | |
| 3 | 2009 | 28 | |
| 4 | 2021 | 23 | |
| 5 | 2022 | 23 | |
| 6 | 2020 | 18 | |
| 7 | 2020 | 16 | |
| 8 | 2020 | 14 | |
| 9 | 2022 | 13 | |
| 10 | 2021 | 13 | |
| 11 | 2020 | 12 | |
| 12 | 2021 | 12 | |
| 13 | 2022 | 10 | |
| 14 | 2024 | 8 | |
| 15 | 2018 | 8 | |
| 16 | 2023 | 8 | |
| 17 | 2018 | 7 | |
| 18 | 2021 | 5 | |
| 19 | 2017 | 4 | |
| 20 | 2005 | 4 |
About Bei Hui
Bei Hui is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Radiology, Nuclear Medicine and Imaging, having authored 47 papers that have together received 403 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (15 papers), Topic Modeling (11 papers), AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Text and Document Classification Technologies (3 papers), Advanced Neural Network Applications (3 papers), Complex Network Analysis Techniques (3 papers) and Privacy-Preserving Technologies in Data (3 papers). The work is most often cited by research in Artificial Intelligence (205 citations), Information Systems (107 citations), Computer Vision and Pattern Recognition (87 citations), Complementary and alternative medicine (34 citations) and Statistical and Nonlinear Physics (41 citations). Bei Hui has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Lizong Zhang, Wen Xiao, Ling Tian, Jiajun Qiu, Guangchun Luo, Yue Wu, Xiaobing Zhou, Chen Jia, Xinyan Gao and Weidong Xu. Their work appears in journals such as Expert Systems with Applications, Applied Intelligence, IEEE Internet of Things Journal, Tsinghua Science & Technology and Computer Modeling in Engineering & 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.