Olive’s research centers methods for auditing ML models which use cryptography to keep sensitive information confidential. This improves privacy for those that contribute data, protects intellectual property of ML service providers, and creates avenues for accountability that are otherwise incompatible with the information barriers encountered in real-world ML deployment. Her work has been published in top conferences in machine learning, computer security, and computational biology.

Olive received her PhD in applied cryptography from Northwestern University, a masters’ in ML and computational biology from the University of Maryland, and a bachelors in computer science and biology from Reed College, where she was recently a visiting professor before joining the Vector Institute.