Brandon Reagen

Brandon Reagen is an Assistant Professor in the Department of Electrical and Computer Engineering at New York University, with affiliations in the Computer Science and Engineering Department, the Center for Advanced Technology in Telecommunications (CATT), and the NYU Center for Cybersecurity (CCS). His research focuses on designing specialized hardware accelerators for applications including deep learning and privacy-preserving computation. He has contributed to the development of tools and infrastructure for accelerator design and has published work in conferences related to computer architecture, machine learning, and circuits. Prior to joining NYU, he was a research scientist with Facebook’s AI Infrastructure Research. He earned a PhD in computer science from Harvard in 2018 and holds undergraduate degrees in computer systems engineering and applied mathematics from the University of Massachusetts, Amherst, in 2012.

Brandon Reagen is an Assistant Professor at New York University, specializing in Computer Architecture, Machine Learning, Privacy, and VLSI. His research focuses on developing efficient and secure deep learning accelerators, with an emphasis on low-power, high-accuracy neural network implementations. Reagen's work explores the architectural implications of deep learning systems, including personalized recommendation systems and homomorphic encryption for private inference. He has contributed to frameworks for quantifying neural network resilience and designing accelerators for customized architectures. His research bridges hardware and software, aiming to optimize performance and privacy in large-scale machine learning applications.