Guanyu Li
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Radiology, Nuclear Medicine and Imaging
- Topics
- Advanced Computational Techniques and Applications (22 papers)Advanced Graph Neural Networks (19 papers)Semantic Web and Ontologies (18 papers)
In The Last Decade
Guanyu Li
110 papers receiving 740 citations
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 257
- Computer Networks and Communications 165
- Computer Vision and Pattern Recognition 162
- Information Systems 128
- Radiology, Nuclear Medicine and Imaging 99
Countries citing papers authored by Guanyu Li
This map shows the geographic impact of Guanyu Li'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 Guanyu Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guanyu Li more than expected).
Fields of papers citing papers by Guanyu Li
This network shows the impact of papers produced by Guanyu Li. 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 Guanyu Li. The network helps show where Guanyu Li may publish in the future.
Co-authorship network of co-authors of Guanyu Li
This figure shows the co-authorship network connecting the top 25 collaborators of Guanyu Li. A scholar is included among the top collaborators of Guanyu Li 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 Guanyu Li. Guanyu Li 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 | 2 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 8 | |
| 9 | 3 | |
| 10 | 3 | |
| 11 | 3 | |
| 12 | 4 | |
| 13 | Method of multi-domain information interoperability in semantic Web of things | 0 |
| 14 | Concept distance clustering method of generating fuzzy ontology | 1 |
| 15 | Lattice-tree transforming method of generating rough ontology | 2 |
| 16 | Concept lattice gluing based fuzzy ontology merging method | 0 |
| 17 | Attribute sets power set method of rough formal concept extracting | 1 |
| 18 | Research on K-Means algorithm based on concept lattice | 1 |
| 19 | Semantic Web of things:strategy for Internet of things'intrinsic contradiction | 1 |
| 20 | Researches and Implementation on the Distributed Heterogeneous Data Integration System | 0 |
About Guanyu Li
Guanyu Li is a scholar working on Artificial Intelligence, Signal Processing and Information Systems, having authored 135 papers that have together received 788 indexed citations. Recurring topics across this work include Advanced Computational Techniques and Applications (22 papers), Advanced Graph Neural Networks (19 papers) and Semantic Web and Ontologies (18 papers). The work is most often cited by research in Signal Processing (90 citations), Artificial Intelligence (257 citations) and Computer Vision and Pattern Recognition (162 citations). Guanyu Li has collaborated with scholars based in China, Ireland and Japan. Frequent co-authors include Yinghui Huang, Bo Ning, Shengxian Tu, Xiujuan Zhang, Heng Chen, Peng Wu, Haiying Jiang, Mei Bai, Ding Wang and Di Wang. Their work appears in journals such as Journal of the American College of Cardiology, Scientific Reports and Applied Energy.
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.