Qun Liu
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 5%
- Electrical and Electronic Engineering
- Computational Theory and Mathematics top 10%
- Topics
- Advanced Graph Neural Networks (12 papers)Computational Drug Discovery Methods (8 papers)Machine Learning in Materials Science (7 papers)
- Cited by
- Computer Networks and CommunicationsStatistical and Nonlinear PhysicsStatistics and Probability
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Transactions on Geoscience and Remote Sensing
- Partner nations
- ChinaHong KongUnited Kingdom
In The Last Decade
Qun Liu
56 papers receiving 543 citations
Peers
Comparison fields: 5 of 87
- Computer Networks and Communications 291
- Artificial Intelligence 139
- Statistical and Nonlinear Physics 128
- Electrical and Electronic Engineering 67
- Computational Theory and Mathematics 48
Countries citing papers authored by Qun Liu
This map shows the geographic impact of Qun Liu'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 Qun Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qun Liu more than expected).
Fields of papers citing papers by Qun Liu
This network shows the impact of papers produced by Qun Liu. 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 Qun Liu. The network helps show where Qun Liu may publish in the future.
Co-authorship network of co-authors of Qun Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Qun Liu. A scholar is included among the top collaborators of Qun Liu 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 Qun Liu. Qun Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 0 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 4 | |
| 15 | 9 | |
| 16 | 0 | |
| 17 | 6 | |
| 18 | 14 | |
| 19 | 1 | |
| 20 | 1 |
About Qun Liu
Qun Liu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 68 papers that have together received 562 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (12 papers), Computational Drug Discovery Methods (8 papers) and Machine Learning in Materials Science (7 papers). The work is most often cited by research in Computer Networks and Communications (291 citations), Statistical and Nonlinear Physics (128 citations) and Statistics and Probability (42 citations). Qun Liu has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include Xiaofeng Liao, Songtao Guo, Lianghao Ji, Guoyin Wang, Xiaofeng Liao, Yanbing Liu, Jennifer Chan, Yeh Lam, Lixing Zhu and Yu Wu. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.
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.