Matt’s work focuses on multidisciplinary problems related to cosmology, numerical computing, data analysis, statistics, and machine learning. He has worked on a broad range of topics from image analysis for the Dark Energy Survey to the development of multiple-plane ray tracing algorithms for computing weak gravitational lensing signals from N-body simulations. After spending several years in industry working in data science, his interests now include the application of deep generative modeling techniques to problems in computational cosmology and the use of cosmological simulations as tools for statistical inference.
- B.S., Physics and Mathematics, University of Michigan - Ann Arbor, 2007
- M.S., Physics, University of Chicago, 2008
- Ph.D., Physics, University of Chicago, 2013