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 AI-integrated techniques to problems in computational cosmology and the use of cosmological simulations as tools for statistical inference.

Education

• 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