Shurui Gui
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Explainable Artificial Intelligence (XAI)
- Topic Modeling
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
-
- Advanced Image Processing Techniques
- Advanced Vision and Imaging
Papers in
-
- Advanced Graph Neural Networks 3
- Explainable Artificial Intelligence (XAI) 2
- Adversarial Robustness in Machine Learning 1
- Machine Learning in Healthcare 1
-
- Image Enhancement Techniques 1
- Advanced Image Processing Techniques 1
- Advanced Vision and Imaging 1
- Co-authors
- Hao Yuan (2 shared papers)Shuiwang Ji (3 shared papers)Haiyang Yu (1 shared paper)Chaoyue Wang (1 shared paper)Dacheng Tao (1 shared paper)Jie Wang (1 shared paper)Qicheng Lao (1 shared paper)Kang Li (1 shared paper)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Shurui Gui
3 papers receiving 376 citations
Shurui Gui's Hit Papers
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 239
- Computer Vision and Pattern Recognition 79
- Health Informatics 4
- Signal Processing 30
- Computational Theory and Mathematics 33
Countries citing papers authored by Shurui Gui
This map shows the geographic impact of Shurui Gui'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 Shurui Gui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shurui Gui more than expected).
Fields of papers citing papers by Shurui Gui
This network shows the impact of papers produced by Shurui Gui. 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 Shurui Gui. The network helps show where Shurui Gui may publish in the future.
Co-authors
The 9 scholars most cited alongside Shurui Gui, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Explainability in Graph Neural Networks: A Taxonomic Survey Hit paper breakdown → | 2022 | 331 |
| 2 | 2020 | 50 | |
| 3 | 2023 | 5 | |
| 4 | 2023 | 0 |
About Shurui Gui
Shurui Gui is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Infectious Diseases, Organic Chemistry and Surgery, having authored 4 papers that have together received 386 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (3 papers), Explainable Artificial Intelligence (XAI) (2 papers), Image Enhancement Techniques (1 paper), Adversarial Robustness in Machine Learning (1 paper), Machine Learning in Healthcare (1 paper), Advanced Image Processing Techniques (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Artificial Intelligence (239 citations), Computer Vision and Pattern Recognition (79 citations), Health Informatics (4 citations), Signal Processing (30 citations) and Computational Theory and Mathematics (33 citations). Shurui Gui has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Hao Yuan, Shuiwang Ji, Haiyang Yu, Chaoyue Wang, Dacheng Tao, Jie Wang, Qicheng Lao, Kang Li and Youzhi Luo. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.