AG百家乐代理-红桃KAG百家乐娱乐城_百家乐筹码片_新全讯网网址xb112 (中国)·官方网站

Faculty

中文       Go Back       Search
WU Kailiang
Associate Professor
Associate Professor
wukl@sustech.edu.cn

Employment

◆ 2021.01-present: Associate Professor, Department of Mathematics, Southern University of Science and Technology

◆ 2016.08-2020.12: Postdoctoral Scholar, Department of Mathematics, The Ohio State University

◆ 2016.04-2016.08: Postdoctoral Fellow, Scientific Computing and Imaging Institute, University of Utah

Education

◆ 2011-2016:  Ph.D.  School of Mathematical Sciences, Peking University

◆ 2007-2011:  B.Sc.  School of Mathematics and Statistics, Huazhong University of Science and Technology


Research Interests

◆ Machine Learning and Data-driven Modeling

◆ Numerical Solutions of Partial Differential Equations

◆ Computational Fluid Dynamics and Astrophysics

◆ High-order Accurate Numerical Methods

◆ Hyperbolic Conservation Laws

◆ Approximation Theory and Uncertainty Quantification


Awards

◆ Zhong Jiaqing Mathematics Award, the Chinese Mathematical Society (2019) One of the three major mathematics awards of the Chinese Mathematical Society (4 per 2 years)

◆ Outstanding Ph.D. Graduates Award, PKU (2016)

◆ Outstanding Youth Paper Award (First Prize), the China Society for Computational Mathematics  (2015)

◆ First Prize of "Challenge Cup" May-4th Youth Science Award, PKU (2014)

◆ President Scholarship, PKU (2014–2016) (The biggest scholarship of PKU)


Selected Publications (latest update: May 2021)

◆ 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,    accepted for publication, 2020.


◆ 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.


Professional Services

◆ Reviewer for AMS Mathematical Reviews

◆ Referee for scientific journals including

Communications in Computational Physics

Computer Methods in Applied Mechanics and Engineering

East Asian Journal on Applied Mathematics

Engineering Optimization

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



网上百家乐官网平台下载| 康保县| 百家乐赌局| 金钱豹娱乐| 百家乐官网园蒙特卡罗| 太阳城公司| 百家乐官网群sun811.com| 南宁百家乐赌机| 百家乐官网网娱乐城| 百家乐官网园百乐彩| 大发888网址怎么找| 网上百家乐官网是叫九五至尊么| 八大胜百家乐现金网| 威尼斯人娱乐城真钱百家乐| 足球.百家乐官网投注网出租| 威尼斯人娱乐城官方网站| 网上百家乐官网赌场| 回力百家乐的玩法技巧和规则 | 德州扑克胜率计算器| 百家乐官网在线赌场娱乐网规则 | 线上百家乐技巧| 百家乐官网长龙有几个| 希尔顿百家乐娱乐城 | 百家乐老千| 手机百家乐官网的玩法技巧和规则| 大发888游戏技巧| 24山双山五行的用法| 64风波| 百家乐网站程序| 百家乐官网必胜法hk| 百家乐发牌靴8| 百家乐官网变牌桌| 德州扑克发牌视频| 玩百家乐澳门皇宫娱乐城| 澳门百家乐官网有哪些| tt娱乐城开户| 大杀器百家乐学院| 百家乐官网赌场视屏| 金钻国际娱乐城| 大发888bjl| 米其林百家乐官网的玩法技巧和规则 |