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2024年数学学院“吉大学子全球胜任力提升计划”研究生系列短课程(2024-003)

发表于: 2024-05-29   点击: 

讲座题目:Topics in Image Analysis, AMG and Numerical PDEs

报 告 人:Professor YOUNG JU LEE, Texas State University, USA

报告地点:数学楼天元研讨室6


课程简介:

The course goal is to introduce a couple of topics in image analysis, Algebraic Multigrid Methods and Numerical PDEs. The first five lectures discuss image segmentation by Constrained Normalized Cut and Fair Clustering. This will culminate with a seminar talk on image segmentation. Second five lectures discuss numerical PDEs using discontinuous Galerkin finite element method. In particular, we discuss the coupled flow and transports. This include Darcy’s law and non-Newtonian fluids computations. This also culminates with a seminar talk on a recent result on discontinuous Galerkin finite element methods. The course will be maintained to provide not only algorithmic techniques but also a hands-on experience to implement the algorithms. After students complete the course works, they are expected to have abilities to tackle a number of image analysis problems and solve some hyperbolic problem and elliptic problems.


预备知识:

Advanced Calculus, Linear Algebra and familiarity with differential equations and graph theory. A basic skill to use Matlab is necessary.


报告人简介:

Young Ju Lee is a Professor at Texas State University, Mathematics Department. He obtained his Ph.D degree at Penn State and had a prior faculty position at UCLA and Rutgers, The State University of New Jersey. His expertise is at the development of fast solver for partial differential equations. His current research focuses on development of structure preserving finite element discretization for PDE systems. His research has been funded by National Science Foundation and American Chemical Society. The current research is being funded by Korea Brain Pool program by National Research Foundation of Korea.