◆ 微分方程数值解
◆ 相场模型的数值算法及应用
◆ 非局部模型的数值算法及应用
◆ 2014年，香港浸会大学，数学系，获数学哲学博士学位；
◆ 2010年，浙江大学，数学系，获数学学士学位。
◆ 2018年1月至今，南方科技大学，数学系，副教授 ；
◆ 2017年7月至2018年1月，南方科技大学，数学系，助理教授 ；
◆ 2015年8月至2017年6月，美国哥伦比亚大学，应用物理与应用数学系，博士后；
◆ 2014年8月至2015年8月，美国宾夕法尼亚州州立大学，数学系，博士后。
◆ 2014年，香港浸会大学，亚坤内地研究生奖；
◆ 2014年，第十届东亚工业与应用数学学会学生论文奖。
1. Zhaohui Fu, Tao Tang and Jiang Yang, Energy plus maximum bound preserving Runge–Kutta methods for the Allen–Cahn equation, J. Sci. Comput. 92 (2022), no. 3,Paper No. 97.
2. L. Li, X. Tai and J. Yang, Generalization Error Analysis of Neural Networks with the Gradient-Based Regularization, to appear on CiCP, 2022.
3. T. Tang, X. Wu and J. Yang, Arbitrarily high order and fully discrete extrapolated RK–SAV/DG schemes for phase-field gradient flows, J. Sci. Comput. 93 (2022), no. 2,Paper No. 38.
4. F. Li and J. Yang, A rigorously provable efficient monotonic-decaying scheme for shape optimization in Stokes flows with phase-field approaches, Comput. Methods Appl. Mech.Engrg. 398 (2022), Paper No. 115195, 24 pp.
5. Z. Fu and J. Yang, Energy plus strong stability preserving Runge–Kutta methods for the Allen–Cahn equation, J. Comput. Phys., 454(2022), pp. 110943.
6. T. Tang, B. Wang and J. Yang, Asymptotic analysis on the sharp interface limit of the time-fractional Cahn–Hilliard equation, to appear in SIAM J. App. Math., 82 (2022),no. 3, 773792..
7. J. Yang, Z. Yuan, and Z. Zhou, Arbitrarily High-order Maximum Bound Preserving Schemes with Cut-off Postprocessing for Allen-Cahn Equations, J. Sci. Comput., 90 (2022), no. 2, Paper No. 76, 36 pp.
8. Lili Ju, Xiao Li, Zhonghua Qiao and Jiang Yang, Maximum bound principle preserving integrating factor Runge–Kutta methods for semilinear evolution equations,J. Comput. Phys., 439 (2021), pp. 110405.
9. J. Yang and Q. Zhu, A Local Deep Learning Method for Solving High Order Partial Differential Equations, Numer. Math. Theory Methods Appl., 15 (2022), no. 1, 4267.
10. Lingfeng Li, Shousheng Luo, Xuecheng Tai and Jiang Yang, A new variational approach based on level-set function for convex hull problem with outliers, Inverse Probl.Imaging 15 (2021), no. 2, 315–338.
11. L. Li, S. Luo, X. Tai and J. Yang, A Level Set Representation Method for N-dimensional Convex Shape and Applications, Commun. Math. Res., 37 (2021), pp.180-208.
12. Buyang Li, Jiang Yang and Zhi Zhou, Arbitrarily high-order exponential cut-off methods for preserving maximum principle of parabolic equations, SIAM J. Sci. Comput.42 (2020), no. 6, A3957–A3978.
13. Q. Du, J. Yang and Z. Zhou, Time–Fractional Allen–Cahn equation: Analysis and Numerical Methods, J. Sci. Comput. 85 (2020), no. 2.
14. Chaoyu Quan, Tao Tang and Jiang Yang, How to Define Dissipation-Preserving Energy for Time-Fractional Phase-Field Equations, CSIAM Trans. Appl. Math., 1(3) (2020), 478-490.
15. T. Tang and J. Yang, Finding the maximal eigenpair for a large, dense, symmetric matrix based on Mufa Chen’s algorithm, Commun. Math. Res., 36 (2020), 93-112.
16. J. Shen, J. Xu, and J. Yang, A new class of efficient and robust energy stable schemes for gradient flows, SIAM Rev. 61-3 (2019), pp. 474-506.
17. L.F. Li, S. S. Luo, X.C. Tai and J. Yang, A Variational Convex Hull Algorithm, Seventh International Conference on Scale Space and Variational Methods in Computer Vision, 2019, organized by Microsoft Corporation. (Conference paper)
18. Q. Du, Y. Tao, X. Tian and J. Yang, Asymptotically compatible discretization of multidimensional nonlocal diffusion models and approximation of nonlocal Green’s functions, IMA J. Numer. Anal., 39(2) (2019), 607-625.
19. Tao Tang and Jiang Yang, Computing the Maximal Eigenpairs of Large Size Tridiagonal Matrices with O(1) Number of Iterations, Numer. Math. Theor. Meth. Appl.,11 (2018), pp. 877-894.
20. J. Shen, J. Xu, and J. Yang, The scalar auxiliary variable (SAV) approach for gradient flows, J. Comput. Phys., 353 (2018), 407-416.
21. Q. Du, J. Yang, and W. Zhang, Numerical analysis on the uniform L p -stability of Allen-Cahn equations, Int. J. Numer. Anal. Mod., 15(1-2) (2018), 213-227.
22. T. Hou, T. Tang and J. Yang, Numerical analysis of fully discretized Crank–Nicolson scheme for fractional-in-space Allen-Cahn equations, J. Sci. Comput., 72(3) (2017), 1214-1231.
23. Q. Du and J. Yang, Fast and Accurate Implementation of Fourier Spectral Approximations of Nonlocal Diffusion Operators and its Applications, J. Comput. Phys., 332(2017), 118-134.
25. W. Zhang, J. Yang, J. Zhang, and Q. Du, Artifificial boundary conditions for nonlocal heat equations on unbounded domain, Comm. Comp. Phys., 21(1) (2017), 16-39.
26. J. Shen, T. Tang and J. Yang, On the maximum principle preserving schemes for the generalized Allen-Cahn equation, Comm. Math. Sci., 14(6) (2016), 1517-1534.
27. T. Tang and J. Yang, Implicit-explicit scheme for the Allen-Cahn equation preserves the maximum principle, J. Comput. Math., 34(5) (2016), 471-481.
28. Q. Du, Y. Tao, X. Tian and J. Yang, Robust a posteriori stress analysis for approximations of nonlocal models via nonlocal gradients, Comp. Meth. Appl. Mech. Eng. 310(2016), 605-627.
29. Q. Du and J. Yang, Asymptotically compatible Fourier spectral approximations of nonlocal Allen-Cahn equations, SIAM J. Numer. Anal., 54(3) (2016), 1899-1919.
30. X. Feng, T. Tang and J. Yang, Long time numerical simulations for phase-fifield problems using p-adaptive spectral deferred correction methods, SIAM J. Sci. Comput. 37 (2015), A271-A294.
31. X. Feng, T. Tang and J. Yang, Stabilized Crank-Nicolson/Adams-Bashforth schemes for phase field models, East Asian Journal on Applied Mathematics, 3 (2013), pp. 59-80.
