Haijun Yu (于海军)

Professor

• State Key Laboratry of Scientific and Engineering Computing (LSEC)
• Institute of Computational Mathematics and Scientific/Engineering Computing
• Academy of Mathematics and Systems Science
• Chinese Academy of Sciences

  Lanbai Building, No. 55 Zhong-Guan-Cun East Road, Beijing 100190, P. R. China

Phone: +86-10-82541027 Email: hyu AT lsec dot cc DOT ac PT cn

Education

• Ph.D., Computational Mathematics, Peking Univeristy, China 2007
• B.S., Computational Mathematics, Peking University, China, 2002

Employments

• 2010.07 - now Assistant/Associate/Full Professor, Academy of Mathematics and Systems Science
• 2008.01 - 2010.05 Visiting Assistant Professor, Department of Mathematics, Purdue University
• 2007.09 - 2007.12 Postdoctoral Research Associate, PACM, Princeton University

Research Interests

• Spectral methods
• Modelling and numerical analysis of complex fluids
• Numerical methods for high-dimensional PDEs
• Minimum action methods for phase transition computing

Selected Publications

• Xiaoli Chen, Beatrice W. Soh, Zi-En Ooi, Eleonore vissol-Gaudin, Haijun Yu, Kostya S. Novoselov, Kedar Hippalgaonkar, Qianxiao Li, Constructing custom thermodynamics using deep learning, Nature Computational Science 29 Dec, 2023
• Haijun Yu, Itzhak Fouxon, Jianchun Wang, Xiangru Li, Li Yuan, Shipeng Mao, Michael Mond, Lyapunov exponents and Lagrangian chaos suppression in compressible homogeneous isotropic turbulence, Physics of Fluids 35:125114, 2023
• Haijun Yu, Xinyuan Tian, Weinan E, and Qianxiao Li, OnsagerNet: Learning stable and interpretable dynamics using a generalized Onsager principle, Phys. Rev. Fluid 6(11):114402, 2021 arXiv:2009.02327
• Shan Jiang, and Haijun Yu, Efficient Spectral Methods for Quasi-Equilibrium Closure Approximations of Symmetric Problems on Unit Circle and Sphere, J. Sci. Comput 89(2) 43, 2021 arXiv:2104.14206
• Bo Li, Shanshan Tang and Haijun Yu, Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units, Commun. Comput. Phys., 27(2) 379-411, 2020 :Full TexT:
• 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 :Full TexT:
• Xiaoliang Wan and Haijun Yu, Numerical approximation of elliptic problems with log-normal random coefficients, Inter. J. Uncertain. Quan., 9(2) 161-186, 2019 :Full TexT:
• Ling Lin, Haijun Yu and Xiang Zhou, Quasi-Potential Calculation and Minimum Action Method for Limit Cycle, J. Nonlinear Sci. 29(3):961-991, 2019 :Full TexT:
• Xiaoliang Wan, Haijun Yu and Jiayu Zhai, Convergence analysis of finite element approximation of minimum action methods, SIAM J. Numer. Anal. 56(3):1597-1620, 2018 :Full TexT:
• Xianmin Xu, Yana Di and Haijun Yu, Sharp-interface limits of a phase-field model with a generalized Navier slip boundary condition for moving contact lines, J. Fluid Mech._ 748:805-833, 2018 :Full TexT:
• Xiaofeng Yang and Haijun Yu, Efficient second order unconditionally stable schemes for a phase field moving contact line model using an invariant energy quadratization approach, SIAM J. Sci. Comput. 40(3):B889-B914, 2018 :Full TexT:
• Lin Wang and Haijun Yu, On efficient second order stabilized semi-implicit schemes for the Cahn-Hilliard phase-field equation, J. Sci. Comput. 77(2):1185-1209, 2018 :Full TexT:
• Haijun Yu and Xiaofeng Yang, Numerical approximations for a phase-field moving contact line model with variable densities and viscosities, J. Comput. Phys. 334: 665-686, 2017 :Full TexT:
• Xiaoliang Wan and Haijun Yu, A dynamic-solver-consistent minimum action method: With an application to 2d Navier-Stokes equations, J. Comput. Phys. 331:209-226, 2017 :Full TexT:
• Xiaoliang Wan, Haijun Yu and Weinan E, Model the nonlinear instability of wall-bounded shear flows as a rare event: a study on two-dimensional Poiseuille flow, Nonlinearity 28:1409-1440, 2015 :Full TexT:
• Jie Shen, Xiaofeng Yang and Haijun Yu, Efficient energy stable numerical schemes for a phase field moving contact line model, J. Comput. Phys. 284:617-630, 2015 :Full TexT:
• Jie Shen, Li-Lian Wang and Haijun Yu, Approximations by orthonormal mapped Chebyshev functions for higher-dimensional problems in unbounded domains, J. Comput. Appl. Math. 265: 264-275, 2014 :Full TexT:
• Jie Shen and Haijun Yu, On the approximation of Fokker-Planck equation of FENE dumbbell model, I: A new weak formulation and an optimal spectral-Galerkin algorithm in 2-D, SIAM J. Numer. Anal. 50(3): 1136-1161, 2012 :Full TexT:
• Jie Shen and Haijun Yu, Efficient spectral sparse grid methods and applications to high-dimensional elliptic equations II. Unbounded domains, SIAM J. Sci. Comput. 34(2): A1141-A1164, 2012 :Full TexT:
• Feng Chen, Jie Shen and Haijun Yu, A new spectral element method for pricing European options under the Black–Scholes and Merton jump diffusion models, J. Sci. Comput. 52:499-518, 2012 :Full TexT:
• Jie Shen and Haijun Yu, Efficient spectral sparse grid methods and applications to high-dimensional elliptic problems, SIAM J. Sci. Comp. 32(6):3228-3250, 2010 :Full TexT:
• Haijun Yu, Guanghua Ji and Pingwen Zhang, A nonhomogeneous kinetic model of liquid crystal polymers and its thermodynamic closure approximation, Commun. Comput. Phys. 7(2):383-402, 2010 :Full TexT:
• Haijun Yu and Pingwen Zhang, A kinetic-hydrodynamic simulation of microstructure of liquid crystal polymers in plane shear flow, J. Non-Newtonian Fluid Mech. 141:116-127, 2007 :Full TexT:

Teaching

• 2015, 2017, 2018, 2019, 2021 Fall @UCAS: Numerical Methods for Partial Differential Equations II
• 2013 Spring @UCAS: Spectral and High-Order Numerical Methods
• 2008, 2009, 2010, 2011 Spring@Purdue: MATH266, Ordinary Differential Equations
• TA @PKU: 2003 Matlab, Parallel Computing; 2004,2005 Advanced Math; 2005 Functional Analysis

Links

• National Center for Mathematics and Interdisciplinary Sciences, CAS
• Beijing International Center for Mathematical Research
• The Program in Applied and Computational Mathematics at Princeton
• Institute for Mathematics and its Applications
• Institute for Pure and Applied Mathematics