Dr. Tao Zhou (周涛, More pictures)

      Institute of Computational Mathematics and Scientific/Engineering Computing
                                        Academy of Mathematics and Systems Sciences                                    
       Chinese Academy of Sciences
       Beijing 100190, China

Email:  tzhou@lsec.cc.ac.cn    



Research Interests:

* Uncertainty Quantification:  "uncertainty is everywhere",  UQ aims to include uncertainty in mathematical models and quantify its effect on output of interest used in decision making.  UQ has a variety of applications, including hydrology, fluid mechanics, data assimilation, and weather forecasting. 

* Scientific Machine Learning: we mainly focus on deep adaptive sampling strategies with applications to PDEs, generative models with applications to data-driven uncertainty quantification, ect.

* Other topics: Parallel-in-time algorithms,  Fractional PDEs, Phase field models, Numerical FBSDEs, ect.




* East Asia Section of SIAM


* I will write an invited review for Acta Numerica in 2025 (together with M. Gander and  S. Wu).


* Invited Mini-symposia Speaker: SCICADE2024, NUS, Singapore,  July.15-19, 2024.


* Invited Speaker: Workshop on Structure Preserving Methods, PloyU, Hongkong, July.20-24, 2024.


* Main Speaker: 2024年第二届全国数值仿真验证与确认研讨会, 青海, 7月25-28日, 2024.


* Organizer: International Conference on Mathematical Theory of Deep Learning, Beijing, August.5-9, 2024.


* Invited Speaker: 北京师范大学珲春计算数学研讨会, 吉林省珲春市, 8月16日-20日, 2024.


* Invited Mini-symposia Speaker: FrontUQ workshop, Braunschweig, Germany,  Sep.23-27, 2024.




* 第三届王选杰出青年学者奖(北大基金会), 2022


国家高层次人才计划专项, 2022


国家自然科学基金委优秀青年科学基金, 2018. 


中科院青年创新促进会会员, 2018.  (2022年获评优秀会员)


中国工业与应用数学学会青年科技奖, 2016.



Editorial Board


* Associate Editor:  SIAM J Numer Anal.


* Associate Editor:  SIAM J Sci Comput.


* Editorial Board:    J Sci Comput.


*  Associate Editor:  Commun. Comput. Phys.  


Associate Editor:   Int. J. Uncertainty Quantification.


Associate Editor:  Numer. Math: Theor. Meth. Appl. 


*  Editor-in-Chief:     E. Asian J. Appl. Math. 


Associate Editor:  Commun. Math. Res.


Associate Editor:  Annals. Appl. Math. 


Associate Editor:  J. Numer. Math & Comput. Appl. (数值计算与计算机应用)


Editorial Board:   Math. Numer. Sinica (计算数学, 2021-2023


Editorial Board:  信息与计算科学丛书


Editorial Board:  大飞机创新谷学报》(中国商飞)





-- Apr.2022 -- Now,  Professor, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing, China.

-- Jul. 2011-- Mar.2022,  Assistant/Associate professor, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing, China.

-- Sep.2011-Sep.2012,  Postdoc research fellow, CSQI, Department of Mathematics,  Ecole Polytechnique Fédérale de Lausanne ( EPFL),  Switzerland.



* Jan.2012-Dec.2015, High-performance numerical algorithms for SDEs and their applications, NSFC, No.91130003  (Co-PI, RMB 4 Million 重大研究计划重点项目)

* Jan.2013-Dec.2015, Numerical methods for non-linear hyperbolic equations with random parameters, NSFC, No.11201461  (PI, RMB 220, 000, 青年基金)

* Jan.2016-Dec.2016, Muti-symplectic methods and uncertainty quantification for SPDEs, NSFC, No.91530118  (Co-PI, RMB 1 Million, 重大研究计划重点项目延续).

* Jan.2016-Dec.2019, Efficient stochastic collocation methods with applications to uncertainty quantification  NSFC, No.11571351  (PI, RMB 532,000, 面上基金).

* Jan.2017-Dec.2019, Efficient numerical methods for stochastic Hamiltonian PDEs, NSFC, No.91630312  (Co-PI, RMB 3 Million, 重大研究计划集成项目).

* Jan.2017-Dec.2019, Theory and algorithms for the recovery of signals using incomplete measurements, NSFC, No.91630203  (Co-PI, RMB 2 Million, 重大研究计划重点项目).

* Jan.2018-Dec.2022, High order methods for UQ with applications to environement sciences, NSFC,  No. 11731006 (Co-PI, RMB 2.8 Million, 重点项目).

* Jan.2018-Dec.2021, Science challenge project by COSTIND,  No. TZ2018001  (RMB 20 Million,  国防科工委挑战计划,  UQ方向首席科学家).

* Jan.2018-Dec.2022, The national key basic research program,  No. 2018YFB0704304  (Co-PI, 科技部国家重点研发计划).

Jan.2019-Dec.2021, Uncertainty quantification, NSFC, No. 11822111  (PI,  RMB 1.5 Million, 优秀青年科学基金).

* Jan.2020-Dec.2024, The national key R&D program,  No. 2020YFA0712000  (Co-PI, 科技部变革性关键技术).

Jan.2023-Dec.2025,  Youth Innovation Promotion Association (中科院青年创新促进会优秀会员, PI,  RMB 3 Million)

* Jan.2023-Dec.2032,  国家高层次基础人才专项 (PI,  RMB 2 Million/year, up to 20 Million in ten years)

* ...






Dr. Li Zeng (2018-2023),  First job after Ph.D.: Post-doc at EPFL, Switzerland  & Associate Professor at Fuzhou University.


Xiaodong Feng (2019-2024), First job after Ph.D.: Post-doc at UIC Institute for Advanced Study.


Rukang You (2020-2025), Yue Qian (2021-2026), Chenlong Pei (2022-2027), Caolin Tian (2023-2028),  Xuerui Wang (2023-2028), ...


Yuancheng Zhou (Ph.D. from Austilian National University, 2022.07-2024.07), First job after Ph.D.: Assisstant Professor at Shanghai Normal University.


Changyang Tang (Ph.D. from Huazhong University of Science and Technology, 2023.07-2025.07)


Haoqin Wang (Ph.D. from Shanghai Jiaotong University, 2023.09-2025.09)


Shuixin Fang (Ph.D. from Shandong University, 2024.03-2026.03)





88, Qiming Wang, Shuixin Fang, Wenbin Liu and Tao Zhou, A gradient projection method for stochastic optimal control with expected state integral constraint,preprint, 2024.

87,  Xiaodong Feng,  Xiaoliang Wan and Tao Zhou, Physics informed IB-UQ, preprint, 2024.

86,  Xiaodong Feng, Haojiong Zhangguan, Xiaoliang Wan and Tao Zhou, Hybridization of PINN and time finite element method for solving evolution PDEs, preprint, 2024.

85,  Shuxin Fang, Weidong Zhao and Tao Zhou, Analysis of explicit Runge-Kutta schemes for BSDEs, preprint, 2024.

84, Wei Cai,  Shuixin Fang and Tao Zhou, SOC-MartNet: a martingale neural network for the Hamilton-Jacobi-Bellman equation without explicit inf_u(H) in stochastic optimal controls, arXiv:2405.03169v1, 2024.

83, Shulin Wu,  Zihao Yang and Tao Zhou, Mixed precision iterative ParaDiag algorithm, preprint, 2024.

82, Zhiwei Gao, Shulin Wu,  Liang Yan and Tao Zhou, Operator learning based coarse solver for Parareal, preprint, 2024.

81, Zhiwei Gao,  Liang Yan and Tao Zhou,  Adaptive operator learning for infinit-dimensional Bayesian inverse problems,  submitted to SIAM/ASA JUQ, 2023.

80, Xiaoliang Wan, Li Zeng and  Tao Zhou, Bounded KRnet and its applications to density estimation and approximation,  submmited to SIAM J. Sci. Comput., 2023.


79, Jiansong Zhang, Xinxin Guo, Maosheng Jiang, Tao Zhou and Jia Zhao, Linear relaxation method with regularized energy quadratization for phase field models, J. Comput. Phys., 2024.

78, Shulin Wu and Tao Zhou, Convergence analysis for parareal algorithm with non-uniform fine time grids, to appear in SIAM J. Numer. Anal., 2024.

77, Wenbin Liu, Liang Yan, Tao Zhou and Yuancheng Zhou,  Failure-informed adaptive sampling for PINNs, Part III: applications to inverse problems,  to appear in CSIAM Tran. Appl. Math., 2024.

76, Ling Guo, Hao Wu, Yan Wang, Wenwen Zhou and Tao Zhou, IBUQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning, J. Comput. Phys., Vol. 510, 113089, 2024.

75, Xiaoliang Wan, Tao Zhou and Yuancheng Zhou,  Adaptive importance sampling for deep Ritz,  to appear in CAMC, 2024.  (Invited contribution to a special issue in memery of Prof. Zhongci Shi)

74,  Honglin Liao, Tao Tang and Tao Zhou,  Positive definiteness of real quadratic forms resultsing from the variable-step approximations of convolution operators,  Sci. China Math.,  Vol.67, pp. 237-252, 2024.

73, Zhiwei Gao, Tao Tang, Liang Yan and Tao Zhou,  Failure-informed adaptive sampling for PINNs, Part II: combining with re-sampling and subset simulation,  to appear in CAMC, 2024.  (Invited contribution to a special issue for Prof. Remi Abgrall 's 61th birthday)

72,  Xiaoliang Wan, Li Zeng and Tao Zhou,  Adaptive deep density approximation for fractional Fokker-Planck equations,  J. Sci. Comput., 97:68, 2023.

71,  Shulin Wu and Tao Zhou, PinT preconditioner for forward backward evolutionary equations,  SIAM J. Matrix Anal. Appl, Vol. 44, No.4, pp.1771-1798, 2023.

70, Zhiwei Gao, Liang Yan and Tao Zhou,  Failure-informed adaptive sampling for PINNs,  SIAM J. Sci. Comput., Vol. 45, No. 4, pp. A1971- A1994, 2023. 

69,  Honglin Liao, Tao Tang and Tao Zhou,  Stability and convergence of the variable-step time filtered backward Euler scheme for parabolic equations,  BIT Numer. Anal., 63, 39 (2023).

68,  Shuxin Fang, Weidong Zhao and Tao Zhou, Strong stability preserving multistep schemes for FBSDEs,   J. Sci. Comput., 94:53, 2023.

67,  Honglin Liao, Tao Tang and Tao Zhou,  Discrete energy analysis of the third order variable-step BDF scheme for diffusion equations,  J. Comput. Math., 41 (2023), pp. 325-344.

66, Ling Guo, Hao Wu, Xiaochen Yu and Tao Zhou,  Monte Carlo fPINNs: deep learning approach for forward and inverse problems involving high dimensional fractional PDEs, Comput. Methods Appl. Mech. Engrg., (400)2022, 115523.

65,  Shulin Wu, Tao Zhou and Zhi Zhou, A uniform spectral analysis for a preconditioned all-at once system from first-order and second-order evolutionary problems, SIAM J. Matrix Anal. Appl, Vol. 43, No. 3, pp. 1331--1353, 2022.

64, Xiaodong Feng, Li Zeng, and Tao Zhou, Solving time dependent Fokker-Planck equations via temporal normalizing flow, Commu. Comput. Phys., 32 (2022), pp. 401-423 2022.

63, Xu Wang, Weidong Zhao, and Tao Zhou,  Sinc-\theta schemes for backward stochastic differential equations,  SIAM J. Numer. Anal., 60 (4), 1799-1823, 2022.

62, Ling Guo, Hao Wu, and Tao Zhou,  Normalizing field flow: solving forward and inverse stochastic differential equations using physics-informed flow model,  J. Comput. Phys., (461) 2022, 111202.

61 Yabing Sun, Jie Yang, Weidong Zhao, and Tao Zhou, An explicit multistep scheme for mean-field forward backward stochastic differential equations,  J. Comput. Math., (40)2022, 519-543.

60, Jianguo Huang, Haoqin Wang, and Tao Zhou, An augmented Lagrangian deep learning method for variational problems with essential boundary conditions, Commu. Comput. Phys., (31)2022, 966-986.

59, Jun Liu, Xiangsheng Wang, Shulin Wu, and Tao Zhou, A well-conditioned direct PinT algorithm for first- and second-order evolutionary equations, Adv. Comput. Math., (2022) 48:16.

58,  Honglin Liao, Tao Tang and Tao Zhou, A New Discrete Energy Technique for Multi-Step Backward Difference Formulas, CSIAM Tran. Appl. Math., 3 (2022), pp. 318-334.

57,  Honglin Liao, Tao Tang and Tao Zhou,  An energy stable and maximum bound preserving scheme with variable time steps for time fractional Allen-Cahn equation,  SIAM J. Sci. Comput., 43-5, A3503-A3526, 2021.

56, Liang Yan and Tao Zhou,  Stein variational gradient descent with local approximations,  Comput. Methods Appl. Mech. Engrg., (386)2021, 114087.

55Liang Yan and Tao Zhou,  An acceleration strategy for randomize-then-optimize sampling via deep neural networks,  J. Comput. Math.,  39-6, 848-864, 2021.  (A special issue for Numerical methods for high dimensional PDEs and approximations)

54,  Akil Narayan, Liang Yan and Tao Zhou,  Optimal design for kernel interpolation: applications to uncertainty quantification,   J. Comput. Phys., (430)2021, 110094.

53,  Shulin Wu and Tao Zhou,  Parallel implementation of two-stage SDIRK methods via diagonalization,  J. Comput. Phys.,  (428)2021, 110076. 

52,  Honglin Liao, Xuehua Song, Tao Tang and Tao Zhou,  Analysis of the second order BDF scheme with variable steps for the molecular beam epitaxial model without slope selection,  Sci. China Math., 64: 887–902, 2021.

51,  Shulin Wu, Tao Zhou, and Xiaojun Chen, A Gauss-Seidel type method for dynamic nonlinear complementariity problems,  SIAM J. Control. Opti., 58-6, pp. 3389-3412, 2020. 

50,  Richard Archibald, Feng Bao, Jiongmin Yong and Tao Zhou,  An efficient numerical algorithm for solving data drivan feedback control problems,  J. Sci. Comput.,  85(2): 58, 2020.

49,  Liang Yan and Tao Zhou,  Adaptive surrogate modeling based on deep neural networks for large-scale Bayesian inverse problems,  Commu. Comput. Phys., (28)2020, pp.2180-2205. (A special issue for Machine Learning and Scientific Computing)

48,  Honglin Liao, Tao Tang and Tao Zhou,  On energy stable,  maximum-principle preserving, second order BDF scheme with variable steps for the Allen-Cahn equation SIAM J. Numer. Anal., 58(4), pp. 2294-2314, 2020.

47,  Jie Yang, Weidong, Zhao and Tao Zhou,  A unified discretization scheme for FBSDEs: stability, consistency and convergence analysis,  SIAM J. Numer. Anal., 58(4), pp. 2351-2375, 2020.

46,  Shulin Wu and Tao Zhou,   Diagonalization-based paralell-in-time algorithms for parabolic PDE-constrained optimization problemsESAIM COCV,  26 (2020) 88.

45Ling Guo, Akil Narayan, and Tao Zhou,  Constructing least-squares polynomial approximations, SIAM Review, 62(2), 483-508 2020.

44Ling Guo, Akil Narayan, Yongle Liu and Tao Zhou,  Sparse approximation of  data-drien PCEs: an induced sampling approach, Commun. Math. Res., 36:128-153, 2020. (A special issue for UQ)

43,  Honglin Liao, Tao Tang and Tao Zhou,  A second order and nonuniform time-stepping maximum-principle preserving scheme for the time-fractional Allen-Cahn equation, J. Comput. Phys., (414)2020, 109473.

42Tao Tang, Lilian Wang, Huifang Yuan, and Tao Zhou,  Rational  spectral  methods for PDEs involving  fractional Laplacian in unbounded domains,  SIAM J. Sci. Comput., 42-2 (2020), pp. A585-A611.

41,  Yu Fu, Weidong Zhao, and Tao Zhou,  Highly accurate numerical scheme for stochastic optimal control via FBSDEs, Numer. Math. Theor. Meth. Appl., 13 (2020), pp. 296-319, 2020.

40Tao Tang, Haijun Yu and Tao Zhou,  On energy dissipation theory and numerical stability  for time-fractional phase field equations, SIAM J. Sci. Comput. 41-6 (2019), pp. A3757-A3778.

39,  Shulin Wu and Tao Zhou, Acceleration of the MGRiT algorithm via the diagonalization technique, SIAM J. Sci. Comput. 41-5 (2019), pp. A3421-A3448.

38,  Zhiwei Feng, Jichun Li, Tao Tang and Tao Zhou,  Efficient stochastic Galerkin methods for Maxwell's equations with random input,   J. Sci. Comput., 80:248-267, 2019. 

37,  Liang Yan and Tao Zhou,  Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems,  J. Comput. Phys., 381: 110-128, 2019.  

36,  Ling Guo, Yongle Liu, and Tao Zhou,  Data-driven polynomial chaos expansions: a weighted least-squares approximation,  J. Comput. Phys., 381:129-145, 2019.

35,  Jie Yang, Weidong Zhao and Tao Zhou,  Explicit deferred correction methods for second order FBSDEs,   J. Sci. Comput., 79:1409-1432, 2019. 

34Liang Yan and Tao Zhou,  An adaptive multi-fidelity PC-based  ensemble Kalman inversion for inverse problems,   Int. J. Uncertainty Quantif.,  9(3):205-220, 2019.  

33,  Yabing Sun, Weidong Zhao, and Tao Zhou,  An explicit \theta-scheme for mean field forward backward stochastic differential equations,  SIAM J. Numer. Anal., 56(4), 2672–2697, 2018. 

32Ling Guo, Akil Narayan, and Tao Zhou,  A gradient enhanced L_1 mininization for sparse approximation of polynomial chaos expansions,   J. Comput. Phys., 367:49-64, 2018

31,  Shulin Wu, Hui Zhang, and Tao Zhou, Solving time periodic fractional diffusion equations via diagonalization technique and multigridNumer. Linear Algebra Appl., 25(5), e2178, 2018.

30,  Shulin  Wu and Tao Zhou, Parareal algorithms with local time-integrators for time fractional differential equations,  J. Comput. Phys., 358:135-149, 2018.

29,  Zhiqiang Xu and Tao Zhou, A gradient enhanced L_1 approach for the recovery of sparse trigonometric polynomials, Commun. Comput. Phys.,  24 (2018),  pp. 286-308.

28,  Ling Guo, Akil Narayan, Liang Yan, and Tao Zhou,  Weighted approximate Fekete points: sampling for least-squares polynomial approximation, SIAM J. Sci. Comput., 40(1),  A366–A387, 2018.

27, Tao Tang, Huifang Yuan, and Tao Zhou,  Hermite spectral collocation methods for fractional PDEs in unbounded domain,  Commun. Comput. Phys., 24(2018), pp. 1143-1168.  (A special issue for Prof. Houde Han's 80th birthday)

26, Bo Gong, Wenbin Liu, Tao Tang, Weidong Zhao, and  Tao Zhou,  An efficient gradient projection methods for stochastic optimal control problems,  SIAM J. Numer. Anal., 55(6), 2982–3005, 2017.

25,  Yu Fu,  Weidong Zhao and Tao Zhou,  Efficient sparse grid approximations for multi-dimensional coupled  forward backward stochastic differential equations,  DCDS-B, 22(9), pp. 3439-3458, 2017.

24,  John Jakeman, Akil Narayan,  and Tao Zhou,  A generalized sampling and preconditioner scheme for sparse approximation of polynomial chaos expansions,   SIAM J. Sci. Comput.,  39-3,  pp. A 1114 -1144, 2017.

23,  Tao Tang, Weidong Zhao, and Tao Zhou,  Deferred correction methods for forward backward stochastic differential equations Numer. Math. Theor. Meth. Appl., 10(2), pp. 222-242, 2017.  (A special issue for Prof Zhenhuan Teng's 80th birthday)

22,  Akil Narayan, John Jakeman, and Tao Zhou,  A Christoffel function weighted least squares algorithm for collocation approximationsMath. Comput., (86)2017, pp.1913-1947.

21,  Ling Guo, Akil Narayan, Tao Zhou, and Yuhang Chen,  Stochastic collocation methods via L_1 minimization using randomized quadratures SIAM J. Sci. Comput., 39-1, pp. A333-A359, 2017.

20,  Shulin Wu and Tao Zhou, Fast parareal iterations for fractional diffusion equationsJ. Comput. Phys., 329:210-226, 2017.

19,  Tao Kong,  Weidong Zhao, and Tao Zhou,  High order numerical schemes for second order FBSDEs with applications to stochastic optimal control Commun. Comput. Phys., (21)2017,  pp. 808-834.

18,  Yu Fu,  Weidong Zhao, and Tao Zhou,  Multistep schemes for forward backward stochastic differential equations with jumps,   J. Sci. Comput., Volume 69, Issue 2, pp 651–672, 2016.

17,  Hehu Xie and Tao Zhou,  A multilevel finite element method for Fredholm integral eigenvalue problems,   J. Comput. Phys.,  303(2015),  pp. 173-184.

16,  Tao Kong,  Weidong Zhao, and Tao Zhou,  Probabilistic high order numerical schemes for fully nonlinear parabolic PDEsCommun. Comput. Phys.,  (18)2015, pp. 1482-1503.

15,  Eleonora Musharbash, Fabio Nobile and Tao Zhou,  Error analysis of the dynamically orthogonal approximation of time dependent random PDEsSIAM J. Sci. Comput.,  37-2,  pp. A776–A810, 2015.

14,   Akil Narayan and Tao Zhou,  Stochastic collocation methods on unstructured meshes,  Commun. Comput. Phys.,  18(2015),  pp. 1-36.

13,  Tao Zhou, Akil Narayan, and Dongbin Xiu,  Weighted discrete least-squares polynomial approximation using randomized quadraturesJ. Comput. Phys., (298)2015, pp. 787-800.

12,  Shulin Wu and Tao Zhou, Convergence analysis for three parareal solversSIAM J. Sci. Comput. 37-2 (2015), pp. A970-A992.

11, Tao Tang and Tao Zhou,  Discrete least square projection in unbounded domain with random evaluations and its application to parametric uncertainty quantification,  SIAM J. Sci. Comput., 36(5),  pp. A2272–A2295, 2014.

10,  Zhiqiang Xu and Tao Zhou, On sparse interpolation and the design of deterministic interpolation points,  SIAM J. Sci. Comput. 36-4 (2014),  pp. A1752-A1769.

9,   Tao Zhou, Akil Narayan and Zhiqiang Xu,  Multivariate discrete least-squares approximations with a new type of collocation grid,  SIAM J. Sci. Comput., 36-5 (2014),  pp. A2401–A2422.

8,   Weidong Zhao, Yu Fu and Tao Zhou, New kinds of high-order multi-step schemes for forward backward stochastic differential equations,   SIAM J. Sci. Comput. 36-4 (2014),  pp. A1731-A1751.

7,   Tao Zhou, A stochastic collocation method for delay differential equations with random inputAdv. Appl. Math. Mech.,  (6)2014, pp. 403-418,

6,   Zhen Gao and Tao Zhou, Choice of nodal sets for least square polynomial chaos method with application to uncertainty quantificationCommun. Comput. Phys.,   16:365–381, 2014.

5,  Tao Zhou and Tao Tang, Galerkin methods for stochastic hyperbolic problems using bi-orthogonal polynomialsJ. Sci. Comput. 51 (2012), pp.274-292.

4,   Tao Zhou and Tao Tang, Convergence analysis for spectral approximation to a scalar transport equation with a random wave speed,  J. Comput. Math., 30 (2012), pp.643-656.

3,   Tao Zhou,  Stochastic Galerkin methods for elliptic interface problems with random input,  J. Comput. & App. Math., 236(2011) , pp.782-792.

2,   Tao Tang and Tao Zhou, Convergence analysis for stochastic collocation methods to scalar hyperbolic equationsCommun. Comput. Phys., 8(2010), pp.226-248.

1,   Tao Zhou and Tao Tang,  Note on coefficient matrices from stochastic Galerkin methods for random diffusion equations,  J. Comput. Phys., 229 (2010),  pp.8225-8230.


* Scientific Committee: The 17th EASIAM Conference, Macau, June 28-July 1, 2024.

* Organizer: 2024科学与工程计算论坛, 北京, 6月14-16日, 2024.


* Invited Speaker: 偏微分方程正反问题理论与计算研讨会, May 10-12, 中南大学, 长沙, 2024.


* Organizer: 不确定性量化研讨会暨专委会会议, 河南省科学院, 郑州, 5月31日-6月2日, 2024.


* Invited Speaker: 科学与工程计算研讨会, Apr.25-26, 哈尔滨工业大学, 哈尔滨, 2024.


* 《计算数学》和《数值计算与计算机应用》双刊编委会, Apr.26-28, 吉林大学, 长春, 2024.

* 《信息与计算科学丛书》编委会, Apr. 05-07, 浙江大学, 杭州, 2024.

* Invited Speaker: Workshop on inverse problems, Mar.23--24, 北理莫斯科, 深圳, 2024.


* Invited Speaker: 人工智能与计算数学会议, Mar.16--17, 上海交通大学, 2024.


* Invited Mini-symposia Speaker: SIAM UQ24, Trieste, Italy,  Feb.27--Mar.1, 2024.


* Invited Speaker: Workshop on Scientific Computing and Learning, 香港中文大学(深圳), 1月29-30日, 2024.


* Invited Speaker: 图论、优化与科学计算研讨会, 香港理工大学, 12月30-31日, 2023.


* Invited Speaker: 计算数学前沿研讨会, 陕西科技大学, 1月6-7日, 2024.


* Invited Speaker: 科学计算前沿论坛, 厦门大学, 12月1-5日, 2023.


* Invited Speaker: 麓山科学计算论坛, 湖南师范大学, 12月9-10日, 2023.


* Invited Speaker: 反问题及其应用前沿研讨会, 武汉大学,  11月3-5日, 2023.


* Invited Speaker: 科学计算与反问题论坛,  北京师范大学(珠海), 11月10-12日, 2023.


* Invited Speaker: 科学计算研讨会,  四川大学, 11月25-26日, 2023.


* Invited Mini-symposia Speaker: ICIAM2023, Waseda University, Tokyo, Japan,  August 20-25, 2023.


* Organizer: 第三届计算数学研讨会暨足球友谊赛,  中国海洋大学, 青岛, 6月10-11日, 2023.


* Invited Speaker:  机器学习与科学计算研讨会, 复旦大学, 上海, 6月30 --7月1日, 2023


* Invited Mini-symposia Speaker: ICOSAHOM23, Yonsei University, Seoul, August 14-18, Korea.


* Invited Speaker:  计算数学研讨会, 浙江工业大学, 杭州, 5月13-14日, 2023.


* Invited Speaker:  科学与工程问题先进算法研讨会, 上海交通大学, 上海, 5月13-14日, 2023.


* Organizer: 不确定性量化研讨会暨专委会会议, 烟台大学, 烟台, 5月19-21日, 2023.


* Invited Speaker: The 7th international conference on scientific computing and PDEs,  PolyU, HongKong, 5月22-26日, 2023.


* Plenary Speaker: 首届松山湖数学论坛, 东莞, 2月11-12日, 2023


* Plenary Speaker: 第十三届全国随机振动理论与应用学术会议, 大连, 3月24-26日, 2023


* Invited Speaker: 计算数学青年学者论坛, 湘潭大学, 湘潭, 4月1-2日, 2023.


* Plenary Speaker: 湖南省计算数学学会年会, 岳阳, 4月15日, 2023.


* Invited Speaker: 随机微分方程数值计算前沿进展研讨会, 天津师范大学, 4月15-16日, 2023.


* Invited Speaker: Workshop on modeling, algorithm and analysis on complex fluid dynamics, 北京计算科学中心, 4月21-23日, 2023.


* Editorial Board:  计算数学期刊编委会, 湖北宜昌, 4月21-23日, 2023.


* Invited Speaker: 偏微分方程数值方法研讨会(Online), 北京师范大学, 4月22-23日, 2023.


* Invited Speaker: 2022机器学习与科学计算学术研讨会, 武汉大学, 12月9-11日, 2022


* Invited Speaker: International conference on scientific machine learning, Seoul, Korea, August 10-12, 2022

* Invited Mini-symposia Organizer: SciCADE2021, Reykjavík, Iceland, July 25-29, 2022.

* Invited Speaker: ICCM2022, Nanjing, June 27- July 2, 2022.

* Invited Mini-symposia Speaker: SIAM UQ22, Atlanta, USA, April 12-15, 2022.


* Invited  Speaker: Nonlocal and Singular Problems: Recent Advances and Outlook, IMS, Singapore, Feb.28-Mar.4,  2022.


* Invited  Speaker: The 15th EASIAM Annual Conference, Nov.13, 2021.


* Invited  Speaker:  深度学习与偏微分方程数值解,  7月16-18日,  西安交通大学,西安,2021。


* Invited  Speaker:  机器学习与科学计算学术研讨会,  8月6-9日,  武汉大学,武汉,2021。


* Organizer: Workshop on CFD and UQ,  June 25-26,  上海交通大学,上海,2021。


* Invited  Speaker: 科学计算理论与应用,  四川大学,6月25-27日,成都,2021。


* Invited  Speaker: 数值计算方法、理论及应用前沿研讨会(Online),6月26-28日,  香港中文大学--深圳,2021。


* Invited  Speaker:  高精度算法研讨会,  5月15-16日,  南方科技大学,深圳,2021。


* Invited  Speaker:  科学计算与数据分析研讨会,  5月22-23日,  南京信息工程大学,南京,2021。


* Organizer: 不确定性量化专委会会议,  5月29-30日,中南大学,长沙 ,2021。

* Invited Mini-symposia Speaker:  SIAM Conference on Computational Science and Engineering (CSE21), March 1-5, 2021, Texas, USA.

* Mini-symposia Organizer:  18th Annual Meeting of CSIAM, Oct. 29 - Nov.1,  2020, Changsha, Hunan.

* Plenary Speaker:  土木工程中的数据科学,  Aug 18-21,  Xinjiang,  2020


* Invited Speaker:  Online Workshop on Nonlocal Problems,  June. 14-18, Xiamen University and SUSTech, 2020.

* Invited Mini-symposia Speaker:  SIAMUQ20, March. 23-27,  2020, TUM, Germany.

* Invited speaker:  Workshop on "Scientific Computing and Applications"  Feb. 05-10,  2020, NUS, Singapore.

* Invited speaker:  Nonlinear problems: numerics and applications, Jan 12-16, TSIMFSanya, China.


* Invited speaker:  数值方法及其应用研讨会,  Nov. 1-4,  2019, 电子科技大学, 成都.


* Oganizer:   第二届计算数学研讨会暨足球友谊赛,  Oct 19-20,  烟台大学,  山东.


* Mini-symposia Organizer:  17th Annual Meeting of CSIAM, Sep. 19-21,  2019Foshan, Guangdong.


* Invited Speaker:  四川--中亚数学联合会议,  Sep 15-20,  四川大学, 成都.


* Invited Speaker:  Workshop on high dimensional approximations,  Sep 9-13,  Zurich,  Switzerland.

* Oganizer:  UQ热点问题研讨会,  Aug. 23-25,  2019, 天元东北中心, 吉林长春.

* Invited Speaker:  中国科协375次青年科学家论坛,  Aug. 17-18,  Dalian.

* Invited  Speaker:  The third conference on scientific and engineering computing for young Chinese scientists,   Aug. 17-21,  2019Xiangshan, Beijing.

* Plenary Speaker:  第十六届全国微分方程数值方法会议,  Aug 08-11,  Qufu,  Shandong.

* Invited  Mini-symposia Speaker:  ICIAM2019,  July 15-19,  2019,  Valencia, Spain.

* Distinguished Speaker:  The 2019 ShanghaiTech Symposium on Information Science and Technology, June 30 - July 02, 2019, Shanghai.

* Invited  Mini-symposia Speaker:  UNCECOMPJune 24-26,  2019,  Crete,  Greece.

* Invited Speaker:  辐射输运及其相关问题研讨会,  June 21-22, 2019, Shanghai.

* Invited Speaker:  Workshop on machine learning techniques in scientific computing,  June 17-19, 2019, Wuhan.

* Invited Speaker:  International conference on mathematical modeling and numerical methods, May 30 - June 2, 2019, Qingdao.

* Invited Speaker:  The 11th international conference on scientific computing and applications, May 27-30, 2019, Xiamen.

* Plenary Speaker:  重庆工业与应用数学学会2019年会, May 10-12, 2019.

* Mini-symposia Organizer & Invited  Mini-symposia Speaker:  SIAM CSE19 Feb. 25 - Mar. 1,  2019,  Spokane, Washington, USA.

* Invited Speaker:   分数阶建模与数值计算研讨会,  南京航空航天大学, Dec.14-16,  2018.

* Invited Participants:  International workshop on PDE-constrained optimization, optimal control, and applications.  Dec.10-14, TSIMFSanya, China.

* Invited Speaker:   SIAM Student Chapter,  Dec.13, CSRC, Beijing.

* Invited Speaker:  International Workshop on Big Data Challenges for Predictive Modeling of Complex Systems Nov. 26-30,  2018,   Hongkong.

* Invited Speaker  Workshop on Computational Mathematics,  Nov. 8-11,  2018,  Chengdu, China.

* Invited Speaker:   随机动力系统理论与数值方法研讨会,  Oct. 26-28,  2018,  Yantai, China.

* Mini-symposia Organizer:  16th Annual Meeting of CSIAM (中国工业与应用数学学会第16届年会), Sep. 13-16,  2018, Chengdu, China.


* Invited Speaker  The 9th international workshop on PDEs & numerical analysis,  Sep. 9-12,  2018,  Changsha,  China.

* Invited Speaker:   第四届华北-西南计算数学研讨会,  Aug. 27-31,  2018,  Kunming,  China.

* Mini-symposia Organizer:  ICOSAHOM 2018,  9-13 July, 2018, London, UK.


* Organizing Commitee :  International Symposium on Computational Harmonic Analysis,  22-24 June, Beijing, China.


* Invited Speaker 随机算法热点问题研讨会,  天元数学东北中心(吉林大学),  June. 22-24,  2018.


* Invited Speaker  不确定性量化和高性能计算研讨会,  June. 16-17,  2018,  Tongji University,  Shanghai,  China.


* Invited Speaker:   大连理工青年学者星海国际论坛,  Apr. 24-28,  2018,  Dalian,  China.


* Mini-symposia Organizer & Invited  Mini-symposia Speaker:  SIAM UQ18 Apr. 16-19,  2018,  CA, USA.


* Invited Speaker 挑战专题领域一2018年第二批项目实施启动会,  Apr. 9-10,  2018,  Chengdu, China.

* Plenary Speaker  International Conference on Recent Advances in Computational and Applied Mathematics,  Dec.14--17,  2017,  Wuhan University, China

* Invited Speaker From approximation theory to real world applications,  TSIMF  Workshop,  Dec.11--15,  2017,  Sanya, China

* Invited Speaker  HKUST IAS Focused Program on Scientific Computing, Dec.04 --08,  2017,  HKUST,  Hongkong.

* Mini-symposia Organizer:  15th Annual Meeting of CSIAM (中国工业与应用数学学会第15届年会), Oct. 12-14,  2017Qingdao, China.

* Invited Speaker:  最优控制与反问题研讨会,Linyi University,  July 28--30,  2017, Shandong, China

* Invited SpeakerUncertainty quantification in CFD,  Shanghai Jiao Tong University,  July 24--27, 2017,  China.

* Invited SpeakerWorkshop on "UQ and stochastic methods",  CSRC,  June 19--21, Beijing, 2017.

* Invited Speaker航天工业与数学---哈工大航天学院建院三十年,June 11, 哈尔滨,  2017.

* Invited ParticipantsWorkshop on "Probablistic scientific computing: statistical inference approaches to numerical analysis and algorithm design"ICERM,  Brown University,  June 5-9, 2017

* Invited SpeakerInternational Workshop on PDEs: Theory and NumericsMay 11--13, Zhejiang University, Hangzhou, China.

* Invited SpeakerRecent advances in Scientific and Engineering Computation,  Shanghai Jiao Tong University,  May 3--7, 2017,  China.

* Invited Participants第十届中科院--德国洪堡基金会前沿科学研讨会,2017年5月18--21日,德国波茨坦。

* Invited Mini-symposium SpeakerSIAM CSE,  Feb.27--Mar. 3,  2017,  Atlanta, USA.

* Invited Speaker:  Chinese Mathematical Society 2016 Annual meeting (中国数学会2016学术年会),  Sep. 23-26, 2016, Neimeng, China.

* Prize Lecture:  14th Annual Meeting of CSIAM (中国工业与应用数学学会第14届年会), Aug. 12-14,  2016Xiangtan, China.

* Invited Speaker:  最优控制与反问题研讨会,Wuhan UniversityAug.5-7, 2016.

* Invited Speaker:   NSFC-RGC Joint Conference for  Young Chinese Mathematician, July 6-8, 2016. (国家自然科学基金委和香港资助计划局联合青年学者论坛)

* Invited Speaker:  The Tenth International Conference on Scientific Computing and Applications (ICSCA2016), June 6-10, 2016, at the Fields Institute, Toronto, Canada.

* Invited Mini-symposia Speaker: 15th International Conference on Approximation Theory  (AT15)  (San Antonio, TX, USA, May 22-26, 2016)

* Invited Speaker:  Workshop on Stochastic Numerics (by Prof. Peter Kloeden),  HUST,  WuhanApril.16-17,  2016.

* Invited Mini-symposia Speaker:   "Mathematical advances in high-dimensional approximation and integration" at  SIAM conference on Uncertainty Quantification (UQ16) , by Albert Cohen and Clayton Webster.  (EPFL, Lausanne, Switzerland, April 5-8, 2016)

* Mini-symposia Organizer:   "Theoretical and computational advances in collocation approximations for high-dimensional problems" at  SIAM conference on Uncertainty Quantification (UQ16) . Joint with John Jakeman and  Akil Narayan. (EPFL, Lausanne, Switzerland, April 5-8, 2016)

* Invited Participants:  Workshop on "Numerical methods for nonlinear problems" (Tsinghua Sanya International Mathematics Forum (TSIMF) ,  Jan 11-15, 2016)

* Invited Speaker:  Workshop on computational and applied mathematicsMacau University,  Macau, Dec. 12-13,  2015.

* Invited Speaker 计算数学与应用数学青年研讨会 (The 8th Workshop for Young Chinese Computational Mathematicians), Tsinghua University,  Beijing, Nov. 21-22,  2015.

* Organizer & speaker:  Workshop on computation methods and stochastic modelling, Hunan University, Nov 14-15, 2015 (Joint with Prof. L. Jiang).

* Invited SpeakerInternational Workshop on Computational Mathematics and Scientific Computing to honor Max Gunzburger's 70th birthday,  Jeju Island,  South Korea,  August 19-21, 2015.

* Mini-symposia Organizer:   Mini-symposium on "Numerical Analysis for Forward-Backward Stochastic Differential Equations and Related Problems" at the 8th International Congress on Industrial and Applied Mathematics (ICIAM2015).  Joint With Prof. Weidong Zhao from Shandong University.  (Beijing, China, August 10-14, 2015)

* Invited Mini-symposium Speaker:  Mini-symposium on "Reduced-order modeling in uncertainty quantification and computational fluid dynamics" at The 8th International Congress on Industrial and Applied Mathematics (ICIAM2015).  Mini-symposium organized by A. Quarteroni et al.  (Beijing, China, August 10-14, 2015)

* Invited Participants:  Uncertainty quantification in kinetic and hyperbolic problems (KI-Net Conference), University of Wisconsin-Madison, Mar 28-31, 2015 .

* Invited Mini-symposium Speaker:  Mini-symposiums on "Numerical Methods for High-Dimensional Stochastic and Parametric Problems" and "Sparse and compressible representations: Theory, Algorithms and Applications" (two talks) at the SIAM CSE Conference. Mini-symposiums organized by A. Doostan et al. for numerical methods and  J. Jakeman et al. for compressed sensing. (Salt Lake City, Utah, USA, March 14-18, 2015)

* Mini-symposia Organizer:  Mini-symposium on "Numerical Methods for the Stochastic Differential Equations" at the 9th International Conference on Computational Physics (ICCP9).  Joint With Prof. Tiejun Li from Peking University. ( Singapore January 7-11, 2015)

* Invited Speaker:   Workshop on "Recent Advances in Numerical Analysis".  (Shanghai Jiao Tong University, China, November 15-16, 2014)

* Invited Speaker:   International conference on “Recent Advances in Computational Mathematics & Applications”.  (Tsinghua Sanya International Mathematics Forum (TSIMF) , December 8-12, 2014)

* Invited Speaker:  计算数学与应用数学青年研讨会 (The 7th Workshop for Young Chinese Computational Mathematicians.)  (Wuhan University,  China, Dec.12-15, 2014)

* Invited Speaker:  The third International conference on interdisciplinary applied and computational mathematics. (Zhejiang University, China, June 7-10, 2014)

* Invited Mini-symposium Speaker:  Mini-symposium on "High order methods for high-dimensional problems: applications in UQ" at the international conference on spectral and high order methods (ICOSAHOM14). (Salt Lake City, Utah, USA, June 23-27, 2014)

* Invited Mini-symposium Speaker:  Mini-symposium on "Theoretical and numerical analysis for forward-backward stochastic differential equations and stochastic optimal control" at the SIAM conference on UQ. (Savannah, Georgia, USA, Mar.31-Apr.3, 2014)

* Invited Mini-symposium Speaker:   25th Biennial Conference on Numerical Analysis, University of Strathdyde, UK, June 25-28, 2013.

* Invited speaker:   The International Conference on Stochastic Model and Numerical Simulation, Wuhan, Nov. 8-11, 2012

* Invited Mini-symposium Speaker:  Third Chinese-German Workshop on Computational and Applied Mathematics, Sep.28 - Oct.5 2009, University of Heidelberg, Germany.

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