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: deep adaptive sampling strategies with applications to PDEs, generative models with applications to data-driven uncertainty quantification, ect.
* Spectral and high order methods (with applications), Parallel-in-time algorithms, Phase field models, Stochastic optimal control, ect.
News:
* Invited Speaker: International conference on theory and scientific computing of Navier-Stokes, PostTECH, Korea, Jan.13-17, 2025.
* Invited Speaker: Uncertainty quantification in neural network models, BIRS, Banff, Canada, Feb.16-21, 2025.
* Invited Mini-symposia Speaker: UNCECOMP2025, Rhodes island, Greece, June.15-18, 2025.
* Keynote Speaker: ICOSAHOM2025, Montreal, Canada, July.13-18, 2025.
Awards:
* 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: 《计算与应用数学丛书》(科学出版社)
* Editorial Board: 《大飞机创新谷学报》(中国商飞)
Employment:
-- 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.
Grants:
* 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)
* Jan.2025-Dec.2028, NSFC-RGC joint project, No. 12461160275 (PI, RMB 1 Million)
* ...
Students/Post-doc:
Ph.D.:
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), Runyang Wang (2024-2029), ...
Post-doc:
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)
Jiaming Li (Ph.D. from Peking University, 2024.09-2026.09)
Publications:
Submitted:
99, Yang Zhao, Haoyu Lu, Junxiong Jia and Tao Zhou, Functional normalizing flow for statistical inverse problems of PDEs, preprint, 2024.
98, Honglin Liao, Tao Tang, Xuping Wang and Tao Zhou, A class of refined implicit-explicit Runge-Kutta methods with robust adaptibility and unconditional convergence for Cahn-Hilliard model, preprint, 2024.
97, Changyang Tang, Shulin Wu, Tao Zhou and Yuancheng Zhou, Parallel-in-time preconditioner for the time spectral methods, submitted to J. Sci. Comput., 2024.
96, Jianguo Huang, Haohao Wu and Tao Zhou, Adaptive neural network basis methods for PDEs with low-regular solutions, submitted to Commu. Comput. Phys., 2024.
95, Yanyan Wang, Liang Yan and Tao Zhou, Deep learning-enhanced reduced-order ensemble Kalman filter for efficient Bayesian data assimulation of parametric PDEs, submitted to CPC, 2024.
94, Yan Wang, Ling Guo, Hao Wu and Tao Zhou, Energy based diffution generator for efficient sampling of Boltzmann distribution, submitted to Neural Networks, 2024.
93, Wei Cai, Shuixin Fang, Wenzhong Zhang and Tao Zhou, Martingale deep learning for very high dimensional quasi-linear partial differential equations and stochastic optimal controls, arXiv:2408.14395, preprint, 2024.
92, Jizu Huang, Rukang You, and Tao Zhou, Frequency-adaptive multi-Scale deep neural networks, submitted to CMAME, 2024.
91, Kai Du, Yongle Xie, Tao Zhou and Yuancheng Zhou, DeepSPoC: a deep learning based sequential propagation of chaos, preprint, 2024.
90, Xiaodong Feng, Xiaoliang Wan and Tao Zhou, Physics informed IB-UQ, preprint, 2024.
89, Xiaodong Feng, Haojiong Zhangguan, Tao Tang, Xiaoliang Wan and Tao Zhou, Hybridization of PINN and time finite element method for solving evolution PDEs, submitted to J. Comput. Phy., 2024.
88, Shuxin Fang, Weidong Zhao and Tao Zhou, Analysis of explicit Runge-Kutta schemes for BSDEs, submitted to SIAM J. Numer. Anal., 2024.
87, Shulin Wu, Liang Yan, Tao Zhou and Zhi Zhou, Operator learning based coarse solver for Parareal, preprint, 2024.
86, He Zhang, Ran Zhang, and Tao Zhou, A predictor-corrector deep learning algorithm for high dimensional stochastic partial differential equations,submitted to J. Sci. Comput., 2024.
85, Liang Chen, Yaru Chen, Qiuqi Li and Tao Zhou, A dynamical variable-separation method for dynamical systems with random input, submitted to SIAM J. Sci. Comput., 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, submitted to SIAM J. Sci. Comput., 2024.
83, Shulin Wu, Zihao Yang and Tao Zhou, Mixed precision iterative ParaDiag algorithm, submitted to Math. Comput., 2024.
82, Xiaoliang Wan, Li Zeng and Tao Zhou, Bounded KRnet and its applications to density estimation and approximation, submitted to SIAM J. Sci. Comput., 2023.
Published:
81, Martin Gander, Shulin Wu and Tao Zhou, Time parallelization for hyperbolic and parabolic problems, to appear in Acta Numerica, 2025. (Invited Review)
80, Zhiwei Gao, Liang Yan and Tao Zhou, Adaptive operator learning for infinit-dimensional Bayesian inverse problems, SIAM/ASA J. Uncertainty Quantification, Vol. 12, No. 4, pp. 1389-1423, 2024.
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. Phy., 515 (2024) 113225.
78, Shulin Wu and Tao Zhou, Convergence analysis for parareal algorithm with non-uniform fine time grids, SIAM J. Numer. Anal., Vol. 62, No. 5, pp. 2308-2330, 2024.
77, Wenbin Liu, Liang Yan, Tao Zhou and Yuancheng Zhou, Failure-informed adaptive sampling for PINNs, Part III: applications to inverse problems, CSIAM Trans. Appl. Math., 5 (2024), pp. 636-670.
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 Commu. Appl. Math. Comput., 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, Commu. Appl. Math. Comput., Vol.6, pp. 1720-1741, 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.
55, Liang 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 problems, ESAIM COCV, 26 (2020) 88.
45, Ling Guo, Akil Narayan, and Tao Zhou, Constructing least-squares polynomial approximations, SIAM Review, 62(2), 483-508 2020.
44, Ling 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.
42, Tao 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.
40, Tao 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.
34, Liang 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.
32, Ling 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 multigrid, Numer. 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 approximations, Math. 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 equations, J. 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 PDEs, Commun. 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 PDEs, SIAM 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 quadratures, J. Comput. Phys., (298)2015, pp. 787-800.
12, Shulin Wu and Tao Zhou, Convergence analysis for three parareal solvers, SIAM 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 input, Adv. 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 quantification, Commun. Comput. Phys., 16:365–381, 2014.
5, Tao Zhou and Tao Tang, Galerkin methods for stochastic hyperbolic problems using bi-orthogonal polynomials, J. 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 equations, Commun. 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.
Conferences:
* Invited Speaker: The fifth workshop on numerical methods for challenging problems, Nov. 13-15, Xiamen, 2024.
* Invited Speaker: 南方科技大学数学学科发展大会, Nov. 22-24, Shenzhen, 2024.
* Invited Mini-symposia Speaker: FrontUQ workshop, Braunschweig, Germany, Sep.23-27, 2024.
* Invited Speaker: Forum of Numerical Mathematics, Shenzhen, Sep. 13-15, 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.
* Organizer: International Conference on Mathematical Theory of Deep Learning, Beijing, August.5-9, 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.
* Invited Mini-symposia Speaker: SCICADE2024, NUS, Singapore, July.15-19, 2024.
* Invited Speaker: Workshop on Structure Preserving Methods, PloyU, Hongkong, July.20-24, 2024.
* 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, TSIMF, Sanya, 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, 2019，Foshan, 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, 2019, Xiangshan, 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: UNCECOMP, June 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.
* 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, TSIMF, Sanya, 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.
* 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, 2017，Qingdao, China.
* Invited Speaker: 最优控制与反问题研讨会，Linyi University, July 28--30, 2017, Shandong, China
* Invited Speaker：Uncertainty quantification in CFD, Shanghai Jiao Tong University, July 24--27, 2017, China.
* Invited Speaker：Workshop 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 Participants：Workshop on "Probablistic scientific computing: statistical inference approaches to numerical analysis and algorithm design"，ICERM, Brown University, June 5-9, 2017
* Invited Speaker：International Workshop on PDEs: Theory and Numerics，May 11--13, Zhejiang University, Hangzhou, China.
* Invited Speaker：Recent 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 Speaker：SIAM 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, 2016，Xiangtan, China.
* Invited Speaker: 最优控制与反问题研讨会, 武汉大学，Aug.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, Wuhan，April.16-17, 2016.
* Invited Mini-symposia Speaker: SIAM conference on Uncertainty Quantification (UQ16) . (EPFL, Lausanne, Switzerland, April 5-8, 2016)
* Mini-symposia Organizer: SIAM conference on Uncertainty Quantification (UQ16) . (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 mathematics，Macau 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 Speaker: International Workshop on Computational Mathematics and Scientific Computing to honor Max Gunzburger's 70th birthday, Jeju Island, South Korea, August 19-21, 2015.
* Invited Mini-symposium Speaker: 8th International Congress on Industrial and Applied Mathematics (ICIAM2015). (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: SIAM CSE (Salt Lake City, Utah, USA, March 14-18, 2015)
* Mini-symposia Organizer: 9th International Conference on Computational Physics (ICCP9). (Singapore January 7-11, 2015)
* Invited Speaker: Recent Advances in Numerical Analysis. (Shanghai Jiao Tong University, China, November 15-16, 2014)
* Invited Speaker: 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: International conference on spectral and high order methods (ICOSAHOM14). (Salt Lake City, Utah, USA, June 23-27, 2014)
* Invited Mini-symposium Speaker: 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.
Usful Links:
SIAM Journals Math. Comput. J. Comput. Phys. Commun. Comput. Phys. Stoch PDE: Anal Comp J. Sci. Comput.