Matthew Le

Matthew Le has extensive experience in software engineering and AI research, beginning as an Undergraduate Research Assistant at the University of Minnesota from January 2012 to August 2013. Following this role, Matthew worked as a Research Assistant at the Rochester Institute of Technology from August 2013 to August 2016, where Matthew further developed expertise in computer science. Matthew then served as a Software Engineer at the Icahn School of Medicine at Mount Sinai from August 2016 to April 2018 before joining Meta as an AI Research Engineer in April 2018. Currently, Matthew leads the audiobox team at Meta, focusing on generative models for audio, and has contributed to significant projects including the design of a scalable codebase for feature backfilling and the development of Flow Matching, a new generative model. Notably, Matthew is the first author of a paper accepted to NeurIPS 2023 on multilingual speech generation. Education includes a Bachelor of Science in Computer Science from the University of Minnesota-Twin Cities and a Master of Science in Computer Science from the Rochester Institute of Technology.