Brandon Reagen is an Assistant Professor at NYU. His research focuses on developing hardware accelerators and architectures to bridge the immense performance gap of privacy-preserving machine learning. The goal of his work is to demonstrate that technologies like homomorphic encryption can be made feasible. He received his PhD from Harvard in 2018 and, prior to joining NYU, worked as a Research Scientist in FAIR.