Qingchu Wu

832 total citations
43 papers, 644 citations indexed

About

Qingchu Wu is a scholar working on Statistical and Nonlinear Physics, Public Health, Environmental and Occupational Health and Modeling and Simulation. According to data from OpenAlex, Qingchu Wu has authored 43 papers receiving a total of 644 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Statistical and Nonlinear Physics, 23 papers in Public Health, Environmental and Occupational Health and 18 papers in Modeling and Simulation. Recurrent topics in Qingchu Wu's work include Complex Network Analysis Techniques (40 papers), Opinion Dynamics and Social Influence (33 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (23 papers). Qingchu Wu is often cited by papers focused on Complex Network Analysis Techniques (40 papers), Opinion Dynamics and Social Influence (33 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (23 papers). Qingchu Wu collaborates with scholars based in China, Australia and Austria. Qingchu Wu's co-authors include Xinchu Fu, Michael Small, Xin‐Jian Xu, Shufang Chen, Tarik Hadzibeganovic, Huaxiang Liu, Haifeng Zhang, Fei Zhang, Zhaoyan Wu and Yijun Lou and has published in prestigious journals such as Scientific Reports, Physica A Statistical Mechanics and its Applications and Chaos Solitons & Fractals.

In The Last Decade

Qingchu Wu

41 papers receiving 619 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Qingchu Wu China 15 506 293 239 87 66 43 644
Philip E. Paré United States 13 320 0.6× 274 0.9× 220 0.9× 45 0.5× 54 0.8× 64 602
Pierre‐André Noël Canada 11 450 0.9× 144 0.5× 121 0.5× 102 1.2× 60 0.9× 19 562
Zhishuang Wang China 8 567 1.1× 343 1.2× 102 0.4× 158 1.8× 87 1.3× 10 774
Michael A. Andrews Canada 4 230 0.5× 201 0.7× 125 0.5× 121 1.4× 19 0.3× 5 420
Lorenzo Zino Italy 15 302 0.6× 238 0.8× 95 0.4× 136 1.6× 106 1.6× 69 648
Quantong Guo China 11 651 1.3× 290 1.0× 87 0.4× 150 1.7× 100 1.5× 13 835
N. Azimi-Tafreshi Iran 9 211 0.4× 159 0.5× 126 0.5× 51 0.6× 40 0.6× 14 406
David Soriano‐Paños Spain 9 251 0.5× 317 1.1× 117 0.5× 59 0.7× 30 0.5× 30 543
Wen-Jie Bai China 9 505 1.0× 106 0.4× 146 0.6× 52 0.6× 144 2.2× 10 621

Countries citing papers authored by Qingchu Wu

Since Specialization
Citations

This map shows the geographic impact of Qingchu Wu'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 Qingchu Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingchu Wu more than expected).

Fields of papers citing papers by Qingchu Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Qingchu Wu. 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 Qingchu Wu. The network helps show where Qingchu Wu may publish in the future.

Co-authorship network of co-authors of Qingchu Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Qingchu Wu. A scholar is included among the top collaborators of Qingchu Wu 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 Qingchu Wu. Qingchu Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wu, Qingchu & Zhaoyan Wu. (2025). A higher-order interaction model of susceptible-infected-susceptible epidemics on networks with nonlinear microscopic incidence rate. Chaos An Interdisciplinary Journal of Nonlinear Science. 35(5).
2.
Wu, Qingchu, et al.. (2023). Compact pairwise methods for susceptible–infected–susceptible epidemics on weighted heterogeneous networks. Physica A Statistical Mechanics and its Applications. 621. 128805–128805. 3 indexed citations
3.
Wu, Qingchu. (2023). A hybrid one-vertex model for susceptible–infected–susceptible diseases on networks with partial connection information. Chaos Solitons & Fractals. 178. 114370–114370. 1 indexed citations
4.
Wu, Qingchu & Shufang Chen. (2023). Heterogeneous pair-approximation analysis for susceptible–infectious–susceptible epidemics on networks. Chaos An Interdisciplinary Journal of Nonlinear Science. 33(1). 13113–13113. 3 indexed citations
5.
Wu, Qingchu, et al.. (2023). Coupled dynamics of endemic disease transmission and gradual awareness diffusion in multiplex networks. Mathematical Models and Methods in Applied Sciences. 33(13). 2785–2821. 4 indexed citations
6.
Wu, Qingchu & Shufang Chen. (2021). Microscopic edge-based compartmental modeling method for analyzing the susceptible-infected-recovered epidemic spreading on networks. Physical review. E. 104(2). 24306–24306. 2 indexed citations
7.
Wu, Qingchu & Shufang Chen. (2020). Spreading of two interacting diseases in multiplex networks. Chaos An Interdisciplinary Journal of Nonlinear Science. 30(7). 73115–73115. 14 indexed citations
8.
Xiao, Gaoxi, et al.. (2020). Dynamics of opinion formation under majority rules on complex social networks. Scientific Reports. 10(1). 456–456. 16 indexed citations
9.
Wu, Qingchu & Tarik Hadzibeganovic. (2020). An individual-based modeling framework for infectious disease spreading in clustered complex networks. Applied Mathematical Modelling. 83. 1–12. 14 indexed citations
10.
Wu, Qingchu & Tarik Hadzibeganovic. (2018). Pair quenched mean-field approach to epidemic spreading in multiplex networks. Applied Mathematical Modelling. 60. 244–254. 21 indexed citations
11.
Wu, Qingchu & Haifeng Zhang. (2016). Epidemic threshold of node-weighted susceptible-infected-susceptible models on networks. Journal of Physics A Mathematical and Theoretical. 49(34). 345601–345601. 8 indexed citations
12.
Wu, Qingchu, et al.. (2016). Epidemic outbreak for an SIS model in multiplex networks with immunization. Mathematical Biosciences. 277. 38–46. 23 indexed citations
13.
Wu, Qingchu & Yijun Lou. (2016). Local immunization program for susceptible-infected-recovered network epidemic model. Chaos An Interdisciplinary Journal of Nonlinear Science. 26(2). 23108–23108. 6 indexed citations
14.
Wu, Qingchu, Xinchu Fu, Zhen Jin, & Michael Small. (2014). Influence of dynamic immunization on epidemic spreading in networks. Physica A Statistical Mechanics and its Applications. 419. 566–574. 19 indexed citations
15.
Wu, Qingchu, et al.. (2014). Responsive immunization and intervention for infectious diseases in social networks. Chaos An Interdisciplinary Journal of Nonlinear Science. 24(2). 23108–23108. 17 indexed citations
16.
Wu, Qingchu & Shufang Chen. (2014). Epidemic spreading and immunization in node-activity networks. International Journal of Modern Physics C. 26(4). 1550044–1550044. 2 indexed citations
17.
Wu, Zhaoyan, et al.. (2013). Pinning synchronization of complex network with non-derivative and derivative coupling. Nonlinear Dynamics. 73(1-2). 775–782. 32 indexed citations
18.
Wu, Qingchu, Huaxiang Liu, & Michael Small. (2013). Dynamical diversity induced by individual responsive immunization. Physica A Statistical Mechanics and its Applications. 392(12). 2792–2802. 8 indexed citations
19.
Wu, Qingchu, Xinchu Fu, & Meng Yang. (2011). Epidemic thresholds in a heterogenous population with competing strains. Chinese Physics B. 20(4). 46401–46401. 27 indexed citations
20.
Wu, Qingchu. (2010). Global stability of SIS epidemic model with infective medium on complex networks. Journal of systems engineering. 3 indexed citations

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.

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