以第一（或通讯）作者身份发表SCI论文50余篇， 代表性论文如下：

[*] Martin Gander, Shu-Lin Wu*, Tao Zhou. Time parallelization for hyperbolic and parabolic problems. Acta Numerica, Vol. 34, pp. 385-489, 2025. 

2. Shu-Lin Wu, Zihao Yang*.  Mixed precision iterative ParaDiag algorithm, IMA Journal of Numerical Analysis, in revision. 

3. Shu-Lin Wu, Tao Zhou*. Convergence analysis of parareal algorithm with non-uniform fine time grid. SIAM Journal on Numerical Analysis, Vol. 62, No. 5, pp. 2308-2330, 2024

4. Lu Xu, Shu-Lin Wu*. Stability of time-marching MPS–MFS for wave equations. Journal of Scientific Computing.  Vol. 101, Article No. 62, 2024. 

5. Shu-Lin Wu*, Zhiyong Wang and Tao Zhou. PinT Preconditioner for forward-backward evolutionary equations. SIAM Journal on Matrix Analysis and Applications, Vol. 44, No. 4, pp. 1771-1798, 2023.

6. Xiaoqiang Yue, Zhiyong Wang, Shu-Lin Wu*. Convergence analysis of a mixed precision parareal algorithm. SIAM Journal on Scientific Computing, Vol. 45, No. 5, pp. A2483-A2510, 2023.

7. Jun Liu, Shu-Lin Wu*. Parallel-in-time preconditioner for the Sinc-Nystrom method. SIAM Journal on Scientific Computing, Vol. 44 (4), pp. A2386-A2411, 2022

8. Shu-Lin Wu, Tao Zhou, Zhi Zhou*. A uniform spectral analysis for preconditioned all-at-once system from first-order and second-order evolutionary problems. SIAM Journal on Matrix Analysis and Applications, Vol. 44 (4), pp. A2386-A2411, 2022

9. Jun Liu, Xiansheng Wang, Shu-Lin Wu*, Tao Zhou. A well-conditioned direct PinT algorithm for first- and second-order evolutionary equations. Advances in Computational Mathematics, Vol. 48 (16), pp. 1-29, 2022

10. Shu-Lin Wu, Tao Zhou*. Parallel implementation for the two-stage SDIRK methods via diagonalization. Journal of Computational Physics, Vol. 428, Article Number: 110076, 2021.

11. Jun Liu, Shu-Lin Wu*. A fast block α-circulant preconditoner for all-at-once systems from wave equations. SIAM Journal on Matrix Analysis and Applications, Vol. 41(4), pp. 1912-1943, 2020

12. Shu-Lin Wu*, Tao Zhou, Xiaojun Chen. A Gauss-Seidel type method for dynamic nonlinear complementarity problems. SIAM Journal on Control and Optimization, Vol.58-6, pp. 3389-3412, 2020

13. Martin J. Gander, Shu-Lin Wu*. A diagonalization-based parareal algorithm for dissipative and wave propagation problems. SIAM Journal on Numerical Analysis, Vol. 58, pp. 2981–3009, 2020

14. Shu-Lin Wu, Jun Liu*. A parallel-in-time block-circulant preconditioner for optimal control of wave equations. SIAM Journal on Scientific Computing, Vol.42, pp. A1510-A1540, 2020

15. Xian-Ming Gu, Shu-Lin Wu*. A parallel-in-time iterative algorithm for Volterra partial integro-differential problems with weakly singular kernel. Journal of Computational Physics, Vol. 417, pp. 109576, 2020

16. Shu-Lin Wu, Tao Zhou*. Diagonalization-based parallel-in-time algorithms for parabolic PDE-constrained optimization problems. ESAIM Control Optimisation and Calculus of Variations, Vol. 26, pp. 88, 2020

17. Shu-Lin Wu*, Tao Zhou. Acceleration of the two-level MGRIT algorithm via the diagonalization technique. SIAM Journal on Scientific Computing, Vol. 41(5), pp. A3421-A3448, 2019

18. Martin J. Gander, Shu-Lin Wu*. Convergence analysis of a periodic-like waveform relaxation method for initial-value problems via the diagonalization technique. Numerische Mathematik，Vol. 143(2), pp. 489-527, 2019

19. Shu-Lin Wu*, Chengming Huang. Asymptotic results of Schwarz waveform relaxation algorithm for time fractional Cable equations. Communications in Computational Physics, Vol. 25, pp. 390-415, 2019

20. Shu-Lin Wu*. Towards parallel coarse grid correction for the parareal algorithm. SIAM Journal on Scientific Computing, Vol.40, pp. A1446–A1472, 2018

21. Shu-Lin Wu*, Hui Zhang, Tao Zhou. Solving time-periodic fractional diffusion equations via diagonalization technique and multi-grid. Numerical Linear Algebra with Applications,Vol.25, e2178, 2018

22. Shu-Lin Wu, Tao Zhou*. Parareal algorithms with local time-integrators for time fractional differential equations. Journal of Computational Physics, Vol. 358, pp. 135-149, 2018

23. Shu-Lin Wu*, Yingxiang Xu. Convergence analysis of Schwarz waveform relaxation with convolution transmission conditions. SIAM Journal on Scientific Computing, Vol. 39, pp. A890-A921, 2017

24. Shu-Lin Wu*, Xiaojun Chen. A parallel iterative algorithm for differential linear complementarity problems. SIAM Journal on Scientific Computing, Vol.39, pp. A3040-A306, 2017

25. Shu-Lin Wu, Tao Zhou*. Fast parareal iterations for fractional diffusion equations. Journal of Computational Physics, Vol. 329, pp. 210–226, 2017

26. Shu-Lin Wu*. Optimized overlapping Schwarz waveform relaxation for a class of time-fractional diffusion problems. Journal of Scientific Computing, Vol.72 (2), pp. 842–862, 2017

27. Shu-Lin Wu*, Mohammad Al-Khaleel. Optimized waveform relaxation methods for RC circuits: discrete case. ESAIM: Mathematical Modelling and Numerical Analysis, Vol. 51, pp. 209–223, 2017

28. Shu-Lin Wu*, M. D. Al-Khaleel. Parameter optimization in waveform relaxation for fractional-order RC circuits. IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 64 (7), pp. 1781-1790, 2017

29. Shu-Lin Wu*. A second-order parareal algorithm for fractional PDEs. Journal of Computational Physics, Vol.307, pp. 280-290, 2016

30. Shu-Lin Wu*. Convergence analysis of Parareal-Euler algorithm for ODEs systems with complex eigenvalues. Journal of Scientific Computing, Vol. 67, pp. 644-668, 2016

31. Shu-Lin Wu*, Tao Zhou. Convergence analysis of three parareal solvers. SIAM Journal on Scientific Computing, Vol.37, pp. A970–A992, 2015

32. Shu-Lin Wu*. Convergence analysis of some second-order Parareal algorithms. IMA Journal of Numerical Analysis, Vol.35, pp. 1315-1341, 2015

33. Shu-Lin Wu*, Mohammad D. Al-Khaleel. Semi-discrete Schwarz waveform relaxation algorithms for reaction diffusion equations. BIT Numerical Mathematics, Vol. 54, pp. 831-866, 2014

34. Shu-Lin Wu*, Ting-Zhu Huang. Schwarz waveform relaxation for a neutral functional partial differential equation model of lossless coupled transmission lines. SIAM Journal on Scientific Computing, Vol. 35, pp. A1161–A1191, 2013

35. Shu-Lin Wu*, Ting-Zhu Huang. Quasi-optimized overlapping Schwarz waveform relaxation algorithm for PDEs with time-delay. Communications in Computational Physics, Vol.14, pp. 780-800, 2013

36. 吴树林*. Robin型离散Schwarz波形松弛算法的收敛性分析. 中国科学A—数学，Vol. 43, pp. 1-24, 2013

37. Shu-Lin Wu*, Chengming Huang, Ting-Zhu Huang. Convergence analysis of the overlapping Schwarz methods for reaction diffusion with time-delay. IMA Journal of Numerical Analysis, Vol. 32, pp. 632-671, 2012

38. Shu-Lin Wu*, Kelin Li. Exponential stability of static neural networks with time delay and impulses. IET Control Theory & Applications, Vol.5, pp. 943-951, 2011

39. Shu-Lin Wu, Baochang Shi, Chengming Huang*. Parareal-Richardson algorithm for solving nonlinear ODEs and PDEs. Communications in Computational Physics, Vol. 6, pp. 883-902, 2009

湖北省优秀博士论文                                       2011

中国科协”青年人才托举工程“                       2016

四川省杰出青年基金                                       2016

国家数学天元东北中心”优秀青年学者“       2021

吉林省”青年拔尖人才“                                   2021

国家高层次青年人才                                      2023

研究工作得到以下基金资助（主持）

1. 弱耗散微分方程两种PinT算法收敛性研究 (No. 12571419, 2026.01-2029.12),  国家自然科学基金-面上项目

2. 几类时间依赖微分方程 Parareal 算法收敛性研究（No. 12171080，2022.01-2025.12), 国家自然科学基金-面上项目

3. 大规模延迟微分方程组卷积Schwarz波形松弛算法收敛性研究（No.11771313, 2018.01-2021.12),国家自然科学基金-面上项目

4. 几类延迟常微分方程的 Schwarz 型波形松弛算法研究（No. 11301362, 2014.01-2016.12)，国家自然科学基金-青年基金

5. Robin 型离散 Schwarz 波形松弛算法的收敛性分析 (No. 11226312，2013.01-2013.12), 国家自然科学基金-数学天元基金

6. 两类延迟微分方程的parareal算法收敛性分析（No. 2015M580777, 2015.09-2017.08)，中国博士后科学基金-面上项目(一等)

7. 一类初值问题Parareal算法收敛性分析（No.2016T90841, 2016.09-2018.08), 中国博士后科学基金-特别资助

8. 非局部演化大规模电路系统快速计算方法研究（No.2018JY0469, 20180.07-2021.07)，四川省科技厅面上项目

9. 波传导方程新型时间并行算法研究（No.JC010284408, 2022.01-2024.12), 吉林省自然科学基金-自由探索类基础研究项目

(1) 波动方程时间并行计算方法
Parareal和MGRIT是一类时间层面的多格子算法，是当前时间并行计算研究领域最流行的算法，非常适用于发展方程的快速计算。Parareal、MGRIT及其相关算法对强耗散问题（如热传导问题）数值计算有显著加速效果。对弱耗散问题，如对流占优扩散方程，算法的收敛速度随耗散性的减弱持续变差。对纯波传导方程，如声波方程和Schrodinger方程，Parareal和MGRIT均不收敛。Diagonalization-in-time是课题组独立提出的一类全新时间并行计算方法（算法名称为ParaDiag)。基于国家天河-1号超算平台的大规模计算结果表明，该算法对耗散问题和纯波传导问题均有十分可观的加速效果，且加速比明显高于Parareal和MGRIT。近年来，我们针对几类具有代表性的波传导问题，获得了此类算法完整的谱分析和收敛速度估计，并得到了此类算法收敛性和Runge-Kutta方法稳定性之间的本质联系。

(2) 发展方程(Schwarz) Waveform Relaxation算法
此项研究关注的重点是设计卷积型-SOR迭代和卷积型传输条件，使得Waveform Relaxation算法具有常数收敛因子。我们主要感兴趣不同离散卷积公式对算法常数收敛因子的影响，以及在实际计算中如何快速实现离散卷积。

(3) 基于Laplace Inversion 技术的时间并行算法
这是一类天然并行的时间并行算法，且不受时间节点分布的影响。不足之处是此类算法只适用于纯线性耗散问题。我们致力于拓展此类时间并行算法在非线性问题中的应用。

(4) 带弱奇异核的Volterra 积分-微分方程快速算法
Volterra积分-微分方程是典型的非局部演化发展方程，实际计算需要大量存储空间和不断增加的计算时间。我们致力于探索不同卷积求积公式（特别是Lubich‘s fast convoltion quadratures)在该领域的可能应用，特别关于卷积求积公式和Parareal、Diagonalization-in-time等时间并行算法的结合。

(5) 动态互补问题（DLCP/DNCP）、时间依赖PDE约束优化问题时间并行算法
最优控制问题和互补问题是密切相关的两类问题，在一定数学背景下相互等价。时间依赖PDE约束最优控制问题数值计算通常需要求解一个大规模鞍点代数系统，DLCP/DNCP数值计算需要解决互补变量不光滑问题。我们致力于开发这两类密切相关问题的时间并行算法，并尝试所获结果在转换开关电路系统、期权定价、Signorini渗流问题、波方程优化控制等领域的可能应用。