- Computational and Applied Mathematics
- Approximation Theory
- Machine Learning
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.