Kaixiong Zhou
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Information Systems top 10%
- Molecular Biology
- Co-authors
- Xia HuDaochen ZhaKwei-Herng LaiXin WangXiao HuangZhengyuan XuQingquan SongXin He
- Topics
- Advanced Graph Neural Networks (12 papers)Topic Modeling (8 papers)Recommender Systems and Techniques (5 papers)
- Journals
- Journal of the American Chemical SocietyIEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of Lightwave Technology
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Kaixiong Zhou
39 papers receiving 538 citations
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 336
- Computer Vision and Pattern Recognition 126
- Electrical and Electronic Engineering 86
- Information Systems 84
- Molecular Biology 58
Countries citing papers authored by Kaixiong Zhou
This map shows the geographic impact of Kaixiong 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 Kaixiong Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaixiong Zhou more than expected).
Fields of papers citing papers by Kaixiong Zhou
This network shows the impact of papers produced by Kaixiong 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 Kaixiong Zhou. The network helps show where Kaixiong Zhou may publish in the future.
Co-authorship network of co-authors of Kaixiong Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Kaixiong Zhou. A scholar is included among the top collaborators of Kaixiong Zhou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kaixiong Zhou. Kaixiong Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 4 | |
| 13 | 2 | |
| 14 | Detecting Interactions from Neural Networks via Topological Analysis | 3 |
| 15 | 51 | |
| 16 | 5 | |
| 17 | 6 | |
| 18 | 6 | |
| 19 | 7 | |
| 20 | 2 |
About Kaixiong Zhou
Kaixiong Zhou is a scholar working on Artificial Intelligence, Neurology and Information Systems, having authored 44 papers that have together received 549 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (12 papers), Topic Modeling (8 papers) and Recommender Systems and Techniques (5 papers). The work is most often cited by research in Artificial Intelligence (336 citations), Computer Vision and Pattern Recognition (126 citations) and Information Systems (84 citations). Kaixiong Zhou has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Xia Hu, Daochen Zha, Kwei-Herng Lai, Xin Wang, Xiao Huang, Zhengyuan Xu, Qingquan Song, Xin He, Ying Wang and Rui Chen. Their work appears in journals such as Journal of the American Chemical Society, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Lightwave Technology.
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.