Mailing address: see http://ww1.math.nus.edu.sg/contactus.aspx
Office: National University of Singapore, S17-08-15
Email: matyh at nus dot e d u dot s g
Assistant Professor 2017-
Department of Mathematics
National University of Singapore
Visiting Assistant Professor 2015-2017
Department of Mathematics
Ph.D. in Mathematics 2012-2015
Advisor: Lexing Ying
M.s. in Mathematics 2010-2012
the University of Texas at Austin
B.s. in Mathematics 2006-2010
Shanghai Jiao Tong University, China
Advisor: Zhenli Xu
Organizing SIAM Conference on Imaging Science 2018 Minisymposium: Low-Dimensional Structures in Imaging Science
Many objects of interest in imaging science exhibit a low-dimensional structure, which could mean, for instance, low sparsity of a vector, low-rank property of a large matrix, or low-dimensional manifold model for a data set. Many successful methods rely on deep understanding and clever exploitation of such low-dimensional structures. The goal of this mini-symposium is to bring together researchers actively working on imaging techniques based on low-dimensional models, and to explore some recent state-of-the-art work in scientific computation, machine learning and optimization related with imaging science. Section 1, Section 2, Section 3.
Organizing SIAM Conference on Applied Linear Algebra 2018 Minisymposium: Large-Scale Eigenvalue Problems and Applications
Eigenvalue problem is the essential part and the computationally intensive part in many applications in a variety of areas, including, electron structure calculation, dynamic systems, machine learning, etc. In all these areas, efficient algorithms for solving large-scale eigenvalue problems are demanding. Recently many novel scalable eigensolvers were developed to meet this demand. The choice of an eigensolver highly depends on the properties and structure of the application. This minisymposium in- vites eigensolver developers to discuss the applicability and performance of their new solvers. The ultimate goal is to assist computational specialists with the proper choice of eigensolvers for their applications. Section 1, Section 2.
ButterflyLab is a MATLAB toolbox for fast evaluation of multidimensional Fourier integral operators for wave equations and a class of transforms in harmonic analysis. Algorithms in this package are based on the comprementary low-rank structure of the matrix representations of these opertors and transforms. The butterfly algorithm or butterfly factorization is able to evaluate the matrix-vector multiplication with nearly linear operation and memory complexity. This MATLAB package is available at Codes.