Aaron Defazio

New York City, United States

Aaron's research focuses on improving the practice of machine learning through the development of more reliable and theoretically sound methods such as performance optimization, initialization, and normalization. He also drives current research frontiers in applied areas and is currently involved in MRI imaging reconstruction and automated theorem proving.