姓名：

张凯

性别：

男

职称：

教授

所在系别：

计算数学系

是否博导：

是

最高学历：

博士研究生毕业

最高学位：

博士

电话：

15143199887

Email：

zhangkaimath@jlu.edu.cn

所在学科专业：

Applied and computational mathematics

所研究方向：

Numerical methods for stochastic Helmholtz and Maxwell equation.

Option pricing and arbitrage.

讲授课程：

Computational method

Scientific Computational method

Scientific modeling and its realization
Finite element method for PDE (postgraduate)

Former PhD : Benxi Zhu, Haiming Song, Qi Zhang, Jingshi Li, Jiachuan Zhang, Yongle Hao, Jinda Yang, Xiaowei Pang

Current PhD: Yu Gao, Yiyuan Qian, Yan Jiang, Xuechen Mu, Fuchang Huo, Jingrong Yang

教育经历：

1995-1999, B.S.,  Computational Mathematics, JLU.
1999-2000, M.S.,  Computational Mathematics, JLU.
2000-2006, Ph.D., Computational Mathematics, JLU.
2003-2008, Jointed Ph.D., Computational Mathematics, CUHK.

工作经历：

2006.09-2011.09, Lecturer, JLU
2008.08-2010.07, Postdoc, MSU
2008.07-2008.08, Visiting Scholar, Department of Mathematics, CUHK
2009.08, Visiting Scholar, Department of Mathematics, IWU
2010.04, Visiting Scholar, Department of Mathematics, AU
2011.09-2015.09, Associate Professor, JLU
2014.07-2014.08, Visiting Professor, Department of Mathematics, HKBU
2015.09- Now, Professor, JLU

科研项目：

Principal Investigator
1.2006-2007, The Youth Foundation, Jilin University.
2.2008-2010, NSF of China (No.10701039).
3.2011-2013, Forefront of science and interdisciplinary innovation projects of Jilin University.
4.2012-2013, Open Project Program of the State Key Lab of CAD & CG(No.A1302).
5.2014-2015, Scientific research foundation for the returned overseas Chinese scholars.
6.2014-2015, Open project program of the Jilin provincial science and technology department.
7.2015.01-2018.12, NSF of China (No.11471141).
8.2015.01-2017.12, The basic research of the science and technology development program of Jilin province (No.20150101058JC).
9.2018.01-2019.12, The key laboratory of symbolic computation and knowledge engineering of ministry of education, Jilin University (No.93K172018Z01).

10.2019.01-2022.12, NSF of China (No.11871245).

11.2023.01-2026.12, NSF of China (No. 12271207).

Joined
1. 2010-2012, NSF of China (No.10971082), second member.
2. 2010-2013, NSF of China (No.11076014), second member.
3. 2010-2013, NSF of China (No.11071103), second member.

4. 2016-2018, NSAF of China (No.U153010036), third member.

5. 2017.07-2021.06, National Key Research and Development Plan (No.2017YFC06016), Subject.

6. 2017.07-2021.06, National Key Research and Development Plan (No.2017YFC06022), Subject.

学术论文：

Selected SCI paper

1.H.Y. Liu and K. Zhang, Multi-symplectic Runge-Kutta type methods for Hamiltonian wave equations. IMA J. Numer. Anal., 26, 2006, 252-271.

2.Y.P. Lin, K. Zhang and J. Zou, Studies on some perfectly matched layers for one-dimensional time-dependent systems. Adv. Comput. Math., 30, 2009, 1-35.

3.M. Li, S.M. Gao and K. Zhang, Goal-oriented engineering analysis error estimation of design simplification. Comput. Meth. Appl. Mech. Engin, 255, 2013, 89-103.

4.Y.L. Hao, F.D. Kang, J.Z. Li and K. Zhang, A numerical method for Maxwell's equations with random interfaces via shape calculus and pivoted low-rank approximation. J. Comput. Phys., 371, 2018, 1-18.

5.G.Bao, Y.Z. Cao, Y.L. Hao, and K. Zhang, A robust numerical method for the random interface grating problem via shape calculus, weak Galerkin method, and low-rank approximation. J Sci. Comput., 77(1), 2018, 419-442.

6. Y.Gao, H.M. Song, X.S. Wang and K. Zhang, Primal-dual active set method for pricing American better-of option on two assets. Commun. Nonlinear Sci. Numer. Simulat.80 (2020) 104976.

7. M. Li, L.C. Zhu, J.Z. Li and K. Zhang, Efficient optimal design of interconnected anisotropic porous structures using extended triply periodic minimal surfaces. J.Comput. Phys., 425, 2021, 109909.

8.Y. Gao, H.Y. Liu, X.C. Wang and K. Zhang, On an artificial neural network for inverse scattering problems. J. Comput. Phys., 448, 2022, 110771.

9.Y.J. Deng, Y. Jiang, H.Y. Liu and K. Zhang, On new surface-localized transmission eigenmodes. Inverse Probl. Imaging, https://doi.org/10.3934/ipi.2021063

10. Y.J. Ji, Y.H. Zhang, Y.B. Yu, K. Zhang, J. Lin, D.S. Li, and Q. Wu,

Inversion method of a highly generalized neural network based on Rademacher complexity for rough media GATEM data. Trans. Geoscience and Remote Sensing, 60, 2022, 1-12.