講座題目：Topics in Image Analysis, AMG and Numerical PDEs
報 告 人：Professor YOUNG JU LEE， Texas State University, USA
報告地點：數學樓天元研讨室6
課程簡介：
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.
預備知識：
Advanced Calculus, Linear Algebra and familiarity with differential equations and graph theory. A basic skill to use Matlab is necessary.
報告人簡介：
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.
