Andrew Estornell

My research interests fall broadly within the fields of Algorithmic Fairness, Adversarial Machine Learning, Optimization, Game Theory, and Strategic Classification. I enjoy working on problems which can be approached from both theoretical and applied perspectives, especially those which make use of Machine Learning in unconventional or innovative ways, and those which involve interactions between multiple strategic agents.