Xiao‐Bing Zhang
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies 11
- Fractional Differential Equations Solutions 7
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- Mathematical and Theoretical Epidemiology and Ecology Models 22
- Genetics top 10%
- Evolution and Genetic Dynamics 13
- Applied Mathematics top 10%
- Nonlinear Differential Equations Analysis 3
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- Nanoplatforms for cancer theranostics 4
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- Nonlinear Dynamics and Pattern Formation 3
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- Advanced Differential Equations and Dynamical Systems 2
- Co-authors
- Hai‐Feng HuoXin-You MengHong XiangQihong ShiXiaodong WangLiang ZhangShitao LiuAibing Li
- Partner nations
- ChinaIndiaUnited States
In The Last Decade
Xiao‐Bing Zhang
31 papers receiving 516 citations
Peers
Comparison fields: 5 of 71
- Modeling and Simulation 321
- Public Health, Environmental and Occupational Health 439
- Genetics 220
- Applied Mathematics 45
- Statistical and Nonlinear Physics 42
Countries citing papers authored by Xiao‐Bing Zhang
This map shows the geographic impact of Xiao‐Bing Zhang'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 Xiao‐Bing Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiao‐Bing Zhang more than expected).
Fields of papers citing papers by Xiao‐Bing Zhang
This network shows the impact of papers produced by Xiao‐Bing Zhang. 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 Xiao‐Bing Zhang. The network helps show where Xiao‐Bing Zhang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiao‐Bing Zhang, 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 | 2025 | 4 | |
| 2 | 2025 | 11 | |
| 3 | 2025 | 3 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2021 | 1 | |
| 7 | 2021 | 8 | |
| 8 | 2020 | 10 | |
| 9 | 2020 | 36 | |
| 10 | Dynamic behavior of a stochastic SIR epidemic model with vertical transmission | 2019 | 5 |
| 11 | 2019 | 6 | |
| 12 | 2019 | 52 | |
| 13 | 2018 | 41 | |
| 14 | 2018 | 11 | |
| 15 | 2017 | 40 | |
| 16 | 2013 | 2 | |
| 17 | 2011 | 4 | |
| 18 | 2011 | 27 | |
| 19 | 2010 | 3 | |
| 20 | 2009 | 9 |
About Xiao‐Bing Zhang
Xiao‐Bing Zhang is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Genetics, having authored 33 papers that have together received 539 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (22 papers), Evolution and Genetic Dynamics (13 papers), COVID-19 epidemiological studies (11 papers), Fractional Differential Equations Solutions (7 papers), Nanoplatforms for cancer theranostics (4 papers), Nonlinear Differential Equations Analysis (3 papers), Nonlinear Dynamics and Pattern Formation (3 papers) and Advanced Differential Equations and Dynamical Systems (2 papers). The work is most often cited by research in Modeling and Simulation (321 citations), Public Health, Environmental and Occupational Health (439 citations) and Genetics (220 citations). Xiao‐Bing Zhang has collaborated with scholars based in China, India and United States. Frequent co-authors include Hai‐Feng Huo, Xin-You Meng, Hong Xiang, Qihong Shi, Xiaodong Wang, Liang Zhang, Shitao Liu, Aibing Li, Ruijie Liu and Hui Cao.
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.