Iván Ojeda-Ruiz

IOR Research Team is part of the Mathematics Department at Texas State University.

I am mainly interested in Numerical Linear Algebra with applications in Image Processing and Data Clustering. My dissertation thesis was based on Normalized Cut (Ncut) problems with linear constrains. Many methods are used to solve Ncut problems, such as projected power method, lanczos method, augmented Lagrangian Uzawa etc.

I have recently been involved in face recognition and video surveillance applications and have been interested in a few possible frameworks. I mainly use Dynamic Mode Decomposition (DMD), but I am familiar with robust principal component analysis and low rank recovery. Some of the methods used to solve these problems include, Alternating Direction Method, singular value decomposition (SVD) and Cholesky decomposition.

My research group is comprised of undergraduate students who have worked on DMD, Ncut, k-means, RPCA, and SVT. We are interested in applications such as, motion detection, audio files compression, image filtering, detection of lesions, detection of subcortical structures and more.