吴开亮，男，籍贯安徽省安庆市，理学博士，南方科技大学数学系副教授、博士生导师。2011年获华中科技大学数学学士学位；2016年获北京大学计算数学博士学位；2016-2020年先后在美国犹他大学和美国俄亥俄州立大学从事博士后研究工作；2021年1月加入南方科技大学、任副教授。研究方向包括计算流体力学与数值相对论、机器学习与数据驱动建模、微分方程数值解、高维逼近与不确定性量化等。研究成果发表在SINUM，SISC，Numer. Math.，M3AS，J. Comput. Phys.，JSC，ApJS，Phys. Rev. D等期刊上。曾获中国数学会计算数学分会 优秀青年论文奖一等奖（2015）和中国数学会 钟家庆数学奖（2019）。

研究领域

微分方程数值解、计算流体力学与数值相对论、机器学习与数据科学、计算物理、高维逼近论与不确定性量化

荣誉及获奖

◆ 2019：中国数学会 钟家庆数学奖

◆ 2016：北京大学 优秀毕业生

◆ 2015：中国数学会计算数学分会 优秀青年论文奖一等奖

◆ 2014：北京大学 “挑战杯”五四青年科学奖一等奖

代表性论文 （更新于2021年5月）

◆ K. Wu

Positivity-preserving analysis of numerical schemes for ideal magnetohydrodynamics
SIAM Journal on Numerical Analysis,   56(4):2124--2147, 2018.

◆ K. Wu and C.-W. Shu

Provably positive high-order schemes for ideal magnetohydrodynamics: Analysis on general meshes

Numerische Mathematik,   142(4): 995--1047, 2019.

◆ K. Wu and D. Xiu

Data-driven deep learning of partial differential equations in modal space

Journal of Computational Physics,   408: 109307, 2020. 

◆ K. Wu and C.-W. Shu

Provably physical-constraint-preserving discontinuous Galerkin methods for multidimensional relativistic MHD equations

Numerische Mathematik,   accepted for publication, 2021.

◆ K. Wu 

Minimum principle on specific entropy and high-order accurate invariant region preserving numerical methods for relativistic hydrodynamics

submitted for publication, arXiv:2102.03801, 2021.

◆ Z. Chen, V. Churchill, K. Wu, and D. Xiu

Deep neural network modeling of unknown partial differential equations in nodal space

Journal of Computational Physics,     submitted for publication, 2021.

◆ K. Wu and Y. Xing

Uniformly high-order structure-preserving discontinuous Galerkin methods for Euler equations with gravitation: Positivity and well-balancedness

SIAM Journal on Scientific Computing,    43(1), A472--A510, 2021.

◆ K. Wu, T. Qin, and D. Xiu

Structure-preserving method for reconstructing unknown Hamiltonian systems from trajectory data

SIAM Journal on Scientific Computing,   42(6): A3704--A3729, 2020. 

◆ K. Wu and C.-W. Shu

Entropy symmetrization and high-order accurate entropy stable numerical schemes for relativistic MHD equations

SIAM Journal on Scientific Computing,   42(4): A2230--A2261, 2020. 

◆ Z. Chen, K. Wu, and D. Xiu

Methods to recover unknown processes in partial differential equations using data

Journal of Scientific Computing,   85:23, 2020. 

◆ K. Wu, D. Xiu, and X. Zhong

A WENO-based stochastic Galerkin scheme for ideal MHD equations with random inputs 

Communications in Computational Physics,   accepted for publication, 2020.

◆ J. Hou, T. Qin, K. Wu and D. Xiu

A non-intrusive correction algorithm for classification problems with corrupted data

Commun. Appl. Math. Comput.,  in press, 2020.

◆ T. Qin, K. Wu, and D. Xiu

Data driven governing equations approximation using deep neural networks

Journal of Computational Physics,   395: 620--635, 2019.

◆ K. Wu and D. Xiu

Numerical aspects for approximating governing equations using data

Journal of Computational Physics,   384: 200--221, 2019.

◆ K. Wu and C.-W. Shu

A provably positive discontinuous Galerkin method for multidimensional ideal magnetohydrodynamics

SIAM Journal on Scientific Computing,   40(5):B1302--B1329, 2018.

◆ Y. Shin, K. Wu, and D. Xiu

Sequential function approximation with noisy data

Journal of Computational Physics,   371:363--381, 2018.

◆ K. Wu and D. Xiu

Sequential function approximation on arbitrarily distributed point sets

Journal of Computational Physics,   354:370--386, 2018.

◆ K. Wu and H. Tang

On physical-constraints-preserving schemes for special relativistic magnetohydrodynamics with a general equation of state

Z. Angew. Math. Phys.,   69:84(24pages), 2018.

◆ K. Wu, Y. Shin, and D. Xiu

A randomized tensor quadrature method for high dimensional polynomial approximation

SIAM Journal on Scientific Computing,   39(5):A1811--A1833, 2017. 

◆ K. Wu

Design of provably physical-constraint-preserving methods for general relativistic hydrodynamics

Physical Review D,   95, 103001, 2017. 

◆ K. Wu, H. Tang, and D. Xiu

A stochastic Galerkin method for first-order quasilinear hyperbolic systems with uncertainty

Journal of Computational Physics,   345:224--244, 2017. 

◆ K. Wu and H. Tang

Admissible states and physical-constraints-preserving schemes for relativistic magnetohydrodynamic equations

Math. Models Methods Appl. Sci. (M3AS),   27(10):1871--1928, 2017. 

◆ Y. Kuang, K. Wu, and H. Tang

Runge-Kutta discontinuous local evolution Galerkin methods for the shallow water equations on the cubed-sphere grid

Numer. Math. Theor. Meth. Appl.,   10(2):373--419, 2017. 

◆ K. Wu and H. Tang

Physical-constraint-preserving central discontinuous Galerkin methods for special relativistic hydrodynamics with a general equation of state

Astrophys. J. Suppl. Ser. (ApJS),   228(1):3(23pages), 2017. (2015 Impact Factor of ApJS: 11.257)

◆ K. Wu and H. Tang

A direct Eulerian GRP scheme for spherically symmetric general relativistic hydrodynamics

SIAM Journal on Scientific Computing,   38(3):B458--B489, 2016. 

◆ K. Wu and H. Tang

A Newton multigrid method for steady-state shallow water equations with topography and dry areas

Applied Mathematics and Mechanics,   37(11):1441--1466, 2016. 

◆ K. Wu and H. Tang

High-order accurate physical-constraints-preserving finite difference WENO schemes for special relativistic hydrodynamics

Journal of Computational Physics,   298:539--564, 2015.

◆ K. Wu and H. Tang

Finite volume local evolution Galerkin method for two-dimensional relativistic hydrodynamics

Journal of Computational Physics,   256:277--307, 2014. 

◆ K. Wu, Z. Yang, and H. Tang

A third-order accurate direct Eulerian GRP scheme for the Euler equations in gas dynamics

Journal of Computational Physics,   264:177--208, 2014. 

学术服务

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◆ 下列期刊审稿人

Communications in Computational Physics

Computer Methods in Applied Mechanics and Engineering

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Journal of Computational and Applied Mathematics

Journal of Computational Physics

Journal of Scientific Computing

Journal of Applied Mathematics and Computing

Mathematical Models and Methods in Applied Sciences (M3AS)

Mathematica Numerica Sinica

SIAM Journal on Scientific Computing

SIAM/ASA Journal on Uncertainty Quantification