Joseph Daws is a graduate research assistant in the department of mathematics at the University of Tennessee Knoxville working with Professor Clayton Webster. Joseph is interested in problems at the intersection of approximation theory, inverse problems, image processing, optimization, and machine learning. His most recent work is concerned with studying how regularization affects the performance of the optimization problems at the heart of machine learning and image processing.
MS in Mathematics, 2016
University of Tennessee
BS in Mathematics, 2013
University of Tennessee
The spallation neutron source (SNS) is a consumable component which wears out due to radiation damage and cavitation erosion. We propose a spectral clustering based method to detect damage in the target.
Using weighted convex minimization to solve the image inpainting and de-noising problems.