Brett Larsen joined the Flatiron Institute in October 2022 as a Flatiron Research Fellow with a joint appointment in the Centers for Computational Neuroscience and Computational Mathematics. His research focuses on combining theoretical and empirical approaches to better understand deep learning and on designing efficient and effective algorithms to extract insights from neural data. He earned his Ph.D. at Stanford University studying how optimization behaves in the high-dimensional loss landscapes of neural networks and was at the same time a visiting researcher at Sandia National Laboratories working on randomized algorithms for large-scale tensor decompositions. Brett also holds an M.S. in statistics from Stanford, an M.Phil. in scientific computing from the University of Cambridge, and a B.S. in physics and B.S.E. in electrical engineering from Arizona State University.