Left: Me; Right: Gilbert Strang; At SIAM AN18, Portland OR

Simon, Sai-Mang Pun

Blocker 608N

Department of Mathematics, TAMU

College Station TX, 77843

Curriculum Vitae: Click here

MathSciNet: Click here

Math Genealogy Project: Click here

Seminar today: Click here

Quotes

One can know everything about a matrix if one knows the spectrum of this matrix.
Rewriting the equation does not critically change the solution, but it can help our understanding.
A great discovery solves a great problem but there is a grain of disvoery in the solution of any problem.
Happy wife, happy life!

Current Teaching

2020 Spring:

Research interests

My current research interests include numerical analysis for partial differential equations with multiple scales.
The main technique for solving these problems is generalized multiscale finite element method (GMsFEM).
I am also interested in studying the goal-oriented adaptivity within the framework of GMsFEM.

Publications

E. Chung, S. Pollock and S.-M. Pun. Goal-oriented adaptivity of mixed GMsFEM for flows in heterogeneous media. Computer Methods in Applied Mechanics and Engineering, 323 (2017), pp.151-173. Download
E. Chung, S.-M. Pun and Z. Zhang. An adaptive dynamically low-dimensional approximation method for multiscale stochastic diffusion equations. Journal of Computational and Applied Mathematics, 393 (2019), pp.302-313. Download
R. Altmann, E. Chung, R. Maier, D. Peterseim and S.-M. Pun. Computational multiscale methods for linear heterogeneous poroelasticity. arXiv:1801.00615. Accepted by Journal of Computational Mathematics.
E. Chung, S. Pollock and S.-M. Pun. Online basis construction for goal-oriented adaptivity in the GMsFEM. Journal of Computational Physics, 393 (2019), pp.59-73. Download
S. Fu, R. Altmann, E. Chung, R. Maier, D. Peterseim and S.-M. Pun. Computational multiscale methods for linear heterogeneous poroelasticity with high contrast. Journal of Computational Physics, 395 (2019), pp. 286-297. Download
E. Chung and S.-M. Pun. Online adaptive basis enrichment for mixed CEM-GMsFEM. arXiv:1810.10730. Accepted by SIAM Multiscale and Modeling.
E. Chung and S.-M. Pun. Computational multiscale methods for first-order wave equation using CEM-GMsFEM. arXiv:1909.08215.

Past Teaching

2019 Fall:

2019 Spring:	Teaching assistant, MATH2221 Mathematics Laboratory II.
2018 Fall:	Teaching assistant, MATH3290 Mathematical Modeling.
	MATLAB review guide;
	Additional example for Chapter 5.
2018 Spring:	Teaching assistant, MATH2221 Mathematics Laboratory II.
2017 Fall:	Teaching assistant, MATH3290 Mathematical Modeling.
2017 Spring:	Teaching assistant, MATH2230 Complex Variables and applications.
2016 Fall:	Teaching assistant, MATH3290 Mathematical Modeling.
2015 Fall:	Teaching assistant, MATH3290 Mathematical Modeling;
	Teaching assistant, MATH2230 Complex Variables and applications.

Links