My technical 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 intriguing and often unconventional approaches that can be applied to a broad set of areas within artificial intelligence including computer vision, machine learning, and human biometrics. Specifically, my work is looking at open set recognition, extreme value theory models for visual recognition, and biologically-inspired learning algorithms. I’m also a cultural critic and historian, commenting on the social context of emerging technologies from the realistic perspective of a computer scientist.