Shuonan Wu

547 total citations
29 papers, 315 citations indexed

About

Shuonan Wu is a scholar working on Computational Mechanics, Computational Theory and Mathematics and Mechanics of Materials. According to data from OpenAlex, Shuonan Wu has authored 29 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computational Mechanics, 14 papers in Computational Theory and Mathematics and 9 papers in Mechanics of Materials. Recurrent topics in Shuonan Wu's work include Advanced Numerical Methods in Computational Mathematics (21 papers), Advanced Mathematical Modeling in Engineering (13 papers) and Numerical methods in engineering (9 papers). Shuonan Wu is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (21 papers), Advanced Mathematical Modeling in Engineering (13 papers) and Numerical methods in engineering (9 papers). Shuonan Wu collaborates with scholars based in China, United States and Hong Kong. Shuonan Wu's co-authors include Jinchao Xu, Yukun Li, Fei Wang, Qingguo Hong, Zhi Zhou, Wenrui Hao, Michael R. Go, Avner Friedman, Yulong Xing and Ruo Li and has published in prestigious journals such as PLoS ONE, Journal of Computational Physics and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

Shuonan Wu

25 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuonan Wu China 10 194 88 78 77 70 29 315
Cheng Wang Cheng Wang China 11 163 0.8× 27 0.3× 76 1.0× 190 2.5× 70 1.0× 24 343
Claire Chainais-Hillairet France 15 323 1.7× 26 0.3× 154 2.0× 80 1.0× 86 1.2× 38 527
James H. Adler United States 10 234 1.2× 79 0.9× 92 1.2× 30 0.4× 61 0.9× 38 339
Markus Schmuck United Kingdom 9 143 0.7× 58 0.7× 102 1.3× 42 0.5× 17 0.2× 16 308
Carlos Zuppa Argentina 10 136 0.7× 175 2.0× 74 0.9× 19 0.2× 62 0.9× 22 334
Massimiliano Morini Italy 14 141 0.7× 101 1.1× 261 3.3× 116 1.5× 31 0.4× 45 607
Ignacio Tomaš United States 8 280 1.4× 44 0.5× 44 0.6× 53 0.7× 50 0.7× 16 443
Vladimir Shaĭdurov Russia 8 243 1.3× 116 1.3× 88 1.1× 12 0.2× 126 1.8× 24 374
Élie Bretin France 10 119 0.6× 78 0.9× 67 0.9× 112 1.5× 31 0.4× 29 324
Varun Shankar United States 11 254 1.3× 213 2.4× 43 0.6× 16 0.2× 105 1.5× 20 455

Countries citing papers authored by Shuonan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Shuonan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuonan Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Shuonan Wu. A scholar is included among the top collaborators of Shuonan 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 Shuonan Wu. Shuonan 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
2.
Wang, Shun, et al.. (2025). Mathematical Modeling and Solution Landscape Reveal Cancer Progression Dynamics in Tumor Ecological Microenvironment. SIAM Journal on Applied Mathematics. 85(1). 50–77. 2 indexed citations
3.
Wang, Jindong & Shuonan Wu. (2024). Discontinuous Galerkin methods for magnetic advection-diffusion problems. Computers & Mathematics with Applications. 174. 43–54.
4.
Wu, Shuonan, et al.. (2024). A Hybridizable Discontinuous Galerkin Method for Magnetic Advection–Diffusion Problems. Journal of Scientific Computing. 99(3). 1 indexed citations
5.
Borthagaray, Juan Pablo, Ricardo H. Nochetto, Shuonan Wu, & Jinchao Xu. (2023). Robust BPX preconditioner for fractional Laplacians on bounded Lipschitz domains. Mathematics of Computation. 92(344). 2439–2473.
6.
Wu, Shuonan. (2023). Stabilized finite element discretizations of general convection-diffusion problems. Scientia Sinica Mathematica. 54(1). 1–1. 1 indexed citations
7.
Wu, Shuonan, et al.. (2022). A Monotone Discretization for Integral Fractional Laplacian on Bounded Lipschitz Domains: Pointwise Error Estimates under Hölder Regularity. SIAM Journal on Numerical Analysis. 60(6). 3052–3077. 6 indexed citations
8.
Li, Yukun, Shuonan Wu, & Yulong Xing. (2022). Finite Element Approximations of a Class of Nonlinear Stochastic Wave Equations with Multiplicative Noise. Journal of Scientific Computing. 91(2). 6 indexed citations
9.
Borthagaray, Juan Pablo, Ricardo H. Nochetto, Shuonan Wu, & Jinchao Xu. (2021). Robust BPX preconditioner for the integral fractional Laplacian on bounded domains.. arXiv (Cornell University). 1 indexed citations
10.
Wu, Shuonan & Zhi Zhou. (2021). A Parallel-in-Time Algorithm for High-Order BDF Methods for Diffusion and Subdiffusion Equations. SIAM Journal on Scientific Computing. 43(6). A3627–A3656. 7 indexed citations
11.
Wang, Fei, Shuonan Wu, & Jinchao Xu. (2020). A Mixed Discontinuous Galerkin Method for Linear Elasticity with Strongly Imposed Symmetry. Journal of Scientific Computing. 83(1). 12 indexed citations
12.
Wu, Shuonan & Yukun Li. (2019). Analysis of the Morley element for the Cahn–Hilliard equation and the Hele-Shaw flow. ESAIM Mathematical Modelling and Numerical Analysis. 54(3). 1025–1052. 7 indexed citations
13.
Wu, Shuonan, et al.. (2018). New hybridized mixed methods for linear elasticity and optimal multilevel solvers. Numerische Mathematik. 141(2). 569–604. 10 indexed citations
14.
Hao, Wenrui, et al.. (2017). A mathematical model of aortic aneurysm formation. PLoS ONE. 12(2). e0170807–e0170807. 20 indexed citations
15.
Wu, Shuonan & Jinchao Xu. (2017). Multiphase Allen–Cahn and Cahn–Hilliard models and their discretizations with the effect of pairwise surface tensions. Journal of Computational Physics. 343. 10–32. 24 indexed citations
16.
Wu, Shuonan, et al.. (2017). Interior penalty mixed finite element methods of any order in any dimension for linear elasticity with strongly symmetric stress tensor. Mathematical Models and Methods in Applied Sciences. 27(14). 2711–2743. 17 indexed citations
17.
Wu, Shuonan, et al.. (2016). A Second Order Time Homogenized Model for Sediment Transport. Multiscale Modeling and Simulation. 14(3). 965–996. 2 indexed citations
18.
Wu, Shuonan, et al.. (2015). The Lowest Order Interior Penalty Nonconforming Finite Element Methods for Linear Elasticity. arXiv (Cornell University). 1 indexed citations
19.
Li, Ruo & Shuonan Wu. (2013). $$H$$ -adaptive Mesh Method with Double Tolerance Adaptive Strategy for Hyperbolic Conservation Laws. Journal of Scientific Computing. 56(3). 616–636. 3 indexed citations
20.
Wu, Shuonan, et al.. (1995). EXISTENCE OF SOLUTIONS FOR ELLIPTIC INTEGRO-DIFFERENTIAL SYSTEMS. Tamkang Journal of Mathematics. 25(1). 61–70. 2 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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