Noah Amsel is a PhD student in Computer Science at NYU, where he is advised by Joan Bruna and Chris Musco. His degree is supported by an NSF Graduate Research Fellowship. He is affiliated with the Algorithms and Foundations, MaD, and CILVR groups. He is also helps organize the ML-NYC speaker series at the Flatiron Institute. This spring, he is working with John Langford at Microsoft Research on optimization algorithms for pretraining. Noah studies algorithms mathematically. The main themes in his research are linear algebra, approximation theory, and deep learning. He is broadly interested in scientific computing and optimization. Previously, he was a research engineer at Reservoir Labs (now Qualcomm) working on modeling congestion control in communication networks. Before that, he was an undergrad at Yale, where he worked with Bob Frank as part of the CLAY lab and was advised by Dan Spielman. He has spent summers at Adobe Research, Polymathic, and at the Weizmann Institute, the latter working on phylogenetic inference with Boaz Nadler and Ariel Jaffe.