Qiankun Zuo
- Cognitive Neuroscience
- Artificial Intelligence
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging
- Neurology
- Topics
- Functional Brain Connectivity Studies (11 papers)Advanced Neuroimaging Techniques and Applications (7 papers)EEG and Brain-Computer Interfaces (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsIEEE Access
- Partner nations
- ChinaJapanUnited Kingdom
In The Last Decade
Qiankun Zuo
23 papers receiving 264 citations
Hit Papers
Peers
Comparison fields: 5 of 53
- Cognitive Neuroscience 92
- Artificial Intelligence 67
- Computer Vision and Pattern Recognition 64
- Radiology, Nuclear Medicine and Imaging 52
- Neurology 52
Countries citing papers authored by Qiankun Zuo
This map shows the geographic impact of Qiankun Zuo'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 Qiankun Zuo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qiankun Zuo more than expected).
Fields of papers citing papers by Qiankun Zuo
This network shows the impact of papers produced by Qiankun Zuo. 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 Qiankun Zuo. The network helps show where Qiankun Zuo may publish in the future.
Co-authorship network of co-authors of Qiankun Zuo
This figure shows the co-authorship network connecting the top 25 collaborators of Qiankun Zuo. A scholar is included among the top collaborators of Qiankun Zuo 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 Qiankun Zuo. Qiankun Zuo 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 | 1 | |
| 3 | 1 | |
| 4 | Social Image Security with Encryption and Watermarking in Hybrid Domainsbreakdown → | 22 |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 40 | |
| 9 | 23 | |
| 10 | 10 | |
| 11 | Prior-Guided Adversarial Learning With Hypergraph for Predicting Abnormal Connections in Alzheimer’s Diseasebreakdown → | 46 |
| 12 | 3 | |
| 13 | 3 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 32 | |
| 17 | 34 | |
| 18 | 5 | |
| 19 | 12 | |
| 20 | 5 |
About Qiankun Zuo
Qiankun Zuo is a scholar working on Health Informatics, Cognitive Neuroscience and Radiology, Nuclear Medicine and Imaging, having authored 26 papers that have together received 266 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (11 papers), Advanced Neuroimaging Techniques and Applications (7 papers) and EEG and Brain-Computer Interfaces (4 papers). The work is most often cited by research in Neurology (52 citations), Cognitive Neuroscience (92 citations) and Health Informatics (5 citations). Qiankun Zuo has collaborated with scholars based in China, Japan and United Kingdom. Frequent co-authors include Shuqiang Wang, Baiying Lei, C. L. Philip Chen, Huisi Wu, Na Zhong, Michael K. Ng, Yanyan Shen, Yi Pan, Shi Li and Ruiheng Li. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Access.
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.