Shu‐Lin Wu

909 total citations
65 papers, 631 citations indexed

About

Shu‐Lin Wu is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Computational Mechanics. According to data from OpenAlex, Shu‐Lin Wu has authored 65 papers receiving a total of 631 indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Numerical Analysis, 35 papers in Computational Theory and Mathematics and 21 papers in Computational Mechanics. Recurrent topics in Shu‐Lin Wu's work include Numerical methods for differential equations (41 papers), Matrix Theory and Algorithms (31 papers) and Advanced Numerical Methods in Computational Mathematics (20 papers). Shu‐Lin Wu is often cited by papers focused on Numerical methods for differential equations (41 papers), Matrix Theory and Algorithms (31 papers) and Advanced Numerical Methods in Computational Mathematics (20 papers). Shu‐Lin Wu collaborates with scholars based in China, Jordan and United Arab Emirates. Shu‐Lin Wu's co-authors include Tao Tang, Xian‐Ming Gu, Mohammad Al-Khaleel, Jun Liu, Kelin Li, Chengming Huang, Ting‐Zhu Huang, Martin J. Gander, Xinhua Zhang and Baochang Shi and has published in prestigious journals such as Journal of Computational Physics, Journal of the Franklin Institute and SIAM Journal on Numerical Analysis.

In The Last Decade

Shu‐Lin Wu

62 papers receiving 577 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shu‐Lin Wu China 13 374 239 198 163 116 65 631
Hongjiong Tian China 14 389 1.0× 148 0.6× 140 0.7× 46 0.3× 45 0.4× 46 496
Fanwei Meng China 18 236 0.6× 121 0.5× 333 1.7× 38 0.2× 131 1.1× 46 838
Nianyu Yi China 13 221 0.6× 198 0.8× 37 0.2× 385 2.4× 95 0.8× 49 593
Fang Chen China 10 373 1.0× 585 2.4× 31 0.2× 190 1.2× 86 0.7× 48 792
Xuan Zhao China 16 503 1.3× 68 0.3× 610 3.1× 55 0.3× 179 1.5× 59 965
Alan Feldstein United States 14 319 0.9× 150 0.6× 156 0.8× 60 0.4× 34 0.3× 30 533
F. Toutounian Iran 13 373 1.0× 336 1.4× 164 0.8× 85 0.5× 48 0.4× 61 607
S. Mohammad Hosseini Iran 12 284 0.8× 77 0.3× 279 1.4× 44 0.3× 72 0.6× 44 522
Ruslan V. Fedorov Russia 11 296 0.8× 87 0.4× 47 0.2× 191 1.2× 58 0.5× 50 446
Yiqin Lin China 13 232 0.6× 283 1.2× 26 0.1× 75 0.5× 124 1.1× 48 448

Countries citing papers authored by Shu‐Lin Wu

Since Specialization
Citations

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

Fields of papers citing papers by Shu‐Lin Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shu‐Lin Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Shu‐Lin Wu. A scholar is included among the top collaborators of Shu‐Lin 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 Shu‐Lin Wu. Shu‐Lin 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, Shu‐Lin, et al.. (2025). Parallel-in-Time Preconditioner for the Time Spectral Methods. Journal of Scientific Computing. 103(3).
2.
Li, Congcong, et al.. (2024). A Preconditioned MINRES Method for Block Lower Triangular Toeplitz Systems. Journal of Scientific Computing. 100(3). 4 indexed citations
3.
Wu, Shu‐Lin, Zhiyong Wang, & Tao Tang. (2023). PinT Preconditioner for Forward-Backward Evolutionary Equations. SIAM Journal on Matrix Analysis and Applications. 44(4). 1771–1798. 2 indexed citations
4.
Wu, Shu‐Lin, et al.. (2021). A Parallel-in-Time Implementation of the Numerov Method For Wave Equations. Journal of Scientific Computing. 90(1). 8 indexed citations
5.
Wu, Shu‐Lin & Tao Tang. (2020). Diagonalization-based parallel-in-time algorithms for parabolic PDE-constrained optimization problems. ESAIM Control Optimisation and Calculus of Variations. 26. 88–88. 8 indexed citations
6.
Al-Khaleel, Mohammad & Shu‐Lin Wu. (2019). Quasi-overlapping Semi-discrete Schwarz Waveform Relaxation Algorithms: The Hyperbolic Problem. Computational Methods in Applied Mathematics. 20(3). 397–417. 4 indexed citations
7.
Gander, Martin J. & Shu‐Lin Wu. (2019). Convergence analysis of a periodic-like waveform relaxation method for initial-value problems via the diagonalization technique. Numerische Mathematik. 143(2). 489–527. 21 indexed citations
8.
Wu, Shu‐Lin & Chengming Huang. (2019). Asymptotic Results of Schwarz Waveform Relaxation Algorithm for Time Fractional Cable Equations. Communications in Computational Physics. 25(2). 390–415. 1 indexed citations
9.
Wu, Shu‐Lin & Tao Tang. (2016). Fast parareal iterations for fractional diffusion equations. Journal of Computational Physics. 329. 210–226. 23 indexed citations
10.
Wu, Shu‐Lin. (2016). Towards essential improvement for the Parareal-TR and Parareal-Gauss4 algorithms. Journal of Computational and Applied Mathematics. 308. 391–407. 3 indexed citations
11.
Wu, Shu‐Lin. (2015). A second-order parareal algorithm for fractional PDEs. Journal of Computational Physics. 307. 280–290. 4 indexed citations
12.
Wu, Shu‐Lin. (2015). Convergence Analysis of the Parareal-Euler Algorithm for Systems of ODEs with Complex Eigenvalues. Journal of Scientific Computing. 67(2). 644–668. 7 indexed citations
13.
Wu, Shu‐Lin & Tao Tang. (2015). Convergence Analysis for Three Parareal Solvers. SIAM Journal on Scientific Computing. 37(2). A970–A992. 27 indexed citations
14.
Lan, Heng-you, Lecai Cai, & Shu‐Lin Wu. (2012). General hybrid -proximal point algorithm frameworks for finding common solutions of nonlinear operator equations and fixed point problems. Communications in Nonlinear Science and Numerical Simulation. 18(4). 895–904. 1 indexed citations
15.
Wu, Shu‐Lin & Chengming Huang. (2011). Quasi-optimized Schwarz methods for reaction diffusion equations with time delay. Journal of Mathematical Analysis and Applications. 385(1). 354–370. 4 indexed citations
16.
Hu, Peng, Chengming Huang, & Shu‐Lin Wu. (2009). Asymptotic stability of linear multistep methods for nonlinear neutral delay differential equations. Applied Mathematics and Computation. 211(1). 95–101. 12 indexed citations
17.
Wu, Shu‐Lin & Chengming Huang. (2008). Convergence analysis of waveform relaxation methods for neutral differential-functional systems. Journal of Computational and Applied Mathematics. 223(1). 263–277. 3 indexed citations
18.
Wu, Shu‐Lin, et al.. (2008). Newton waveform relaxation method for solving algebraic nonlinear equations. Applied Mathematics and Computation. 201(1-2). 553–560. 9 indexed citations
19.
Wu, Shu‐Lin, Yu‐Chee Tseng, & Jang‐Ping Sheu. (2003). Intelligent medium access for mobile ad hoc networks with busy tones and power control. 71–76. 10 indexed citations
20.
Wu, Shu‐Lin. (1996). APPLICATION OF GENETIC ALGORITHM IN TRAIN LINE HOLDING. Information and Computation. 1 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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