Yifei Lou

Yifei Lou

Associate Professor - Mathematical Sciences
FO 2.408E
Personal webpage
Tags: compressive sensing and its applications image analysis medical imaging hyperspectral imaging imaging through turbulence numerical analysis and optimization algorithms

Professional Preparation

Ph.D - Applied Math
UCLA - 2010
M.S. - Applied Math
UCLA - 2007
B.S. - Applied Math
Peking University - 2005


A Weighted Difference of Anisotropic and Isotropic Total Variation for Relaxed Mumford--Shah Color and Multiphase Image Segmentation 2021 - Journal Article
A Novel Regularization Based on the Error Function for Sparse Recovery 2021 - Journal Article
Blind Hyperspectral Unmixing Based on Graph Total Variation Regularization 2021 - Journal Article
Iteratively Reweighted Group Lasso Based on Log-Composite Regularization 2021 - Journal Article
Limited-Angle CT Reconstruction via the $L_1/L_2$ Minimization 2021 - Journal Article
Probabilistic Structure Learning for EEG/MEG Source Imaging With Hierarchical Graph Priors 2021 - Journal Article
An image sharpening operator combined with framelet for image deblurring 2020 - Journal Article
An Image Sharpening Operator Combined with Framelet for Image Deblurring 2020 - Journal Article




Associate Professor
University of Texas Dallas [2020–Present]
Assistant Professor
University of Texas Dallas [2014–2020]
University of California Irvine [2012–2014]
Georgia Institute of Technology [2011–2012]

News Articles

Mathematician Focuses on Getting the Most from Small Data
Mathematician Focuses on Getting the Most from Small Data A University of Texas at Dallas mathematician has received a five-year grant from the National Science Foundation (NSF) in support of her work on doing more with less data.
Dr. Yifei Lou
, assistant professor of mathematical sciencesin the School of Natural Sciences and Mathematics, was awarded an NSF Faculty Early Career Development (CAREER) Award of more than $400,000 for her work on “Mathematical Modeling for Data to Insights and Beyond,” a project that seeks analytical tools to provide guidance on acquiring data more efficiently. In an age when so much focus is on big data, she calls her work “small data.”

“If one is able to collect only a certain amount of data, what method will allow him or her to get the most out of it?” Lou asked. “For example, if you can see only 25 percent of the pixels in an image, what way of picking one out of every four pixels would let us best identify the pictured object?”


CAREER: Mathematical Modeling from Data to Insights and Beyond
$400,211 - NSF [2019/06–2024/05]