Julian’s research focuses 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.
