My research is primarily focused around the problem of recognition, including the representations and algorithms supporting solutions to it. I am particularly interested in features and learning-based methods that apply to both vision and language, thus breaking away from the persistent compartmentalization of recognition tasks (something hinted at by David Marr over 30 years ago). This has led to some interesting, and
often unconventional approaches that can be applied to a broad set of areas including computer vision,
machine learning, human biometrics, and the digital humanities. Specifically, my work is
looking at open set recognition, extreme value theory models for visual recognition, biologically-inspired learning algorithms, and stylometry.