Can Xu
- Computer Networks and Communications top 5%
- Statistical and Nonlinear Physics top 5%
- Cognitive Neuroscience top 10%
- Biomedical Engineering
- Artificial Intelligence
- Co-authors
- Zhigang ZhengJian GaoShuguang GuanYuting SunStefano BoccalettiPer Sebastian SkardalXiubo GengChongyang Tao
- Topics
- Nonlinear Dynamics and Pattern Formation (39 papers)Neural dynamics and brain function (20 papers)stochastic dynamics and bifurcation (12 papers)
- Cited by
- Computer Networks and CommunicationsStatistical and Nonlinear PhysicsCognitive Neuroscience
- Journals
- Scientific ReportsIEEE Transactions on Geoscience and Remote SensingThe Journal of the Acoustical Society of America
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Can Xu
46 papers receiving 448 citations
Peers
Comparison fields: 5 of 52
- Computer Networks and Communications 358
- Statistical and Nonlinear Physics 179
- Cognitive Neuroscience 160
- Biomedical Engineering 102
- Artificial Intelligence 68
Countries citing papers authored by Can Xu
This map shows the geographic impact of Can Xu'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 Can Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Xu more than expected).
Fields of papers citing papers by Can Xu
This network shows the impact of papers produced by Can Xu. 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 Can Xu. The network helps show where Can Xu may publish in the future.
Co-authorship network of co-authors of Can Xu
This figure shows the co-authorship network connecting the top 25 collaborators of Can Xu. A scholar is included among the top collaborators of Can Xu 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 Can Xu. Can Xu 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 | 2 | |
| 4 | 8 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | 7 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 3 | |
| 11 | 9 | |
| 12 | 41 | |
| 13 | 10 | |
| 14 | 8 | |
| 15 | 5 | |
| 16 | 11 | |
| 17 | 20 | |
| 18 | 19 | |
| 19 | 22 | |
| 20 | 15 |
About Can Xu
Can Xu is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Cognitive Neuroscience, having authored 48 papers that have together received 469 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (39 papers), Neural dynamics and brain function (20 papers) and stochastic dynamics and bifurcation (12 papers). The work is most often cited by research in Computer Networks and Communications (358 citations), Statistical and Nonlinear Physics (179 citations) and Cognitive Neuroscience (160 citations). Can Xu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Zhigang Zheng, Jian Gao, Shuguang Guan, Yuting Sun, Stefano Boccaletti, Per Sebastian Skardal, Xiubo Geng, Chongyang Tao, Xia Huang and Daxin Jiang. Their work appears in journals such as Scientific Reports, IEEE Transactions on Geoscience and Remote Sensing and The Journal of the Acoustical Society of America.
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.