Tiejun Zhou
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 5%
- Public Health, Environmental and Occupational Health
- Applied Mathematics top 10%
- Co-authors
- Yirong LiuAnping ChenGuiping LiaoFang WangYi WangXiaolan ZhangHaiquan FangZhenyun Peng
- Topics
- Neural Networks Stability and Synchronization (16 papers)Neural Networks and Applications (12 papers)Mathematical and Theoretical Epidemiology and Ecology Models (12 papers)
- Cited by
- Modeling and SimulationStatistical and Nonlinear PhysicsComputer Networks and Communications
- Journals
- SHILAP Revista de lepidopterologíaNano LettersAdvanced Functional Materials
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Tiejun Zhou
49 papers receiving 370 citations
Peers
Comparison fields: 5 of 68
- Computer Networks and Communications 174
- Artificial Intelligence 116
- Statistical and Nonlinear Physics 100
- Public Health, Environmental and Occupational Health 59
- Applied Mathematics 49
Countries citing papers authored by Tiejun Zhou
This map shows the geographic impact of Tiejun Zhou'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 Tiejun Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tiejun Zhou more than expected).
Fields of papers citing papers by Tiejun Zhou
This network shows the impact of papers produced by Tiejun Zhou. 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 Tiejun Zhou. The network helps show where Tiejun Zhou may publish in the future.
Co-authorship network of co-authors of Tiejun Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Tiejun Zhou. A scholar is included among the top collaborators of Tiejun Zhou 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 Tiejun Zhou. Tiejun Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 9 | |
| 11 | 4 | |
| 12 | 9 | |
| 13 | 4 | |
| 14 | 7 | |
| 15 | 13 | |
| 16 | 13 | |
| 17 | 12 | |
| 18 | 10 | |
| 19 | 3 | |
| 20 | 22 |
About Tiejun Zhou
Tiejun Zhou is a scholar working on Computational Mathematics, Modeling and Simulation and Numerical Analysis, having authored 57 papers that have together received 386 indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (16 papers), Neural Networks and Applications (12 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (12 papers). The work is most often cited by research in Modeling and Simulation (45 citations), Statistical and Nonlinear Physics (100 citations) and Computer Networks and Communications (174 citations). Tiejun Zhou has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Yirong Liu, Anping Chen, Guiping Liao, Fang Wang, Yi Wang, Xiaolan Zhang, Haiquan Fang, Zhenyun Peng, Chen Li and Yabo Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, Nano Letters and Advanced Functional Materials.
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.