Julian Katz-Samuels



I received my Ph.D. in the electrical and computer engineering at the University of Michigan and my B.A. in mathematics and philosophy at the University of Chicago. I focus on designing practical machine learning algorithms that adaptively collect data to accelerate learning. My recent research interests include active learning, multi-armed bandits, black-box optimization, and out-of-distribution detection using deep neural networks. I am also very interested in machine learning applications that promote the social good. As a fellow at Data Science for Social Good (University of Chicago), I helped develop the Legislative Influence Detector.




jkatzsamuels “at” gmail.com