Yifei Lou

Associate Professor - Mathematical Sciences
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


An Image Sharpening Operator Combined with Framelet for Image Deblurring 2020 - Journal Article
Non-blind and Blind Deconvolution Under Poisson Noise Using Fractional-Order Total Variation 2020 - Journal Article
One-dimensional phase retrieval: regularization, box relaxation and uniqueness 2020 - Journal Article
An image sharpening operator combined with framelet for image deblurring 2020 - Journal Article
Accelerated Schemes for the $L_1/L_2$ Minimization 2020 - Journal Article
Blind Hyperspectral Unmixing Based on Graph Total Variation Regularization 2020 - Journal Article
Task-Related EEG Source Localization via Graph Regularized Low-Rank Representation Model 2018 - Other
Graph Regularized EEG Source Imaging with In-Class Consistency and Out-Class Discrimination 2017 - Journal Article
Fast L1–L2 Minimization via a Proximal Operator 2017 - Journal Article
Image deblurring with an inaccurate blur kernel using a group-based low-rank image prior 2017 - 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
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?”