Director of Scientific Computing
Institute for Physical Science and Technology
University of Maryland, College Park
I obtained my Ph.D. in Applied Mathematics & Statistics, and Scientific Computation from the AMSC program at the University of Maryland, College Park. My area of concentration was Scientific Computation, and my work focused on harmonic analysis and its applications. [Disseration, Dissertation defense slides]
I had the privilege and fortune of having John J. Benedetto as my Ph.D advisor. He is the director of The Norbert Wiener Center for Harmonic Analysis and Applications (NWC). He also directed my M.A. degree work on "Signal processing for health monitoring of jet engines."
I was a post doctoral fellow of the NWC from July 1st, 2012 to June 30, 2013. I continue to collaborate on research projects with faculty of the NWC.
Applications of machine learning to image processing. In particular, applications to super-resolution, inpainting, image segmentation and discovery.
Sparse representations of signals. In specific, implementation, validation and testing of the Orthogonal Matching Pursuit (OMP) and Basis Pursuit (BP) algorithms. A simple description of these algorithms can be found in . I have coded diverse implementations of these algorithms to study image compression, inpainting, and noise removal.
Another area of study that I am interested in is the discovery and study of properties of Constant Amplitude and Zero-Autocorrelation sequences (CAZACs) for use in telecommunications.
 A. M. Bruckstein, D. L. Donoho, and M. Elad, From sparse solutions of systems of equations to sparse modeling of signals and images, SIAM Review, 51 (2009), pp. 34-81.
I obtained First Prize in the poster session "Pushing the Boundaries of Science" at the University of Maryland Graduate Research Interaction Day (GRID) 2012 presenting a poster of my work on "Image representation and compression via sparse solutions of systems of linear equations." [Poster for GRID, Poster for NWC]