Deep Learning

Behavioral Imaging

Naturalistic human behavior presents a complex, multidimensional signal that, while sometime difficult to quantify, is invaluable for understanding and improving human health, development, and everyday functioning. This project aims to develop novel computational methods for measuring and analyzing human behavior to promote scientific and practical advances across a range of disciplines, just as techniques developed for brain imaging have revolutionized neuroscience and medicine. A particular focus of this project is devising new ways to “image” social behavior in children, to better understand and address issues related to atypical patterns of social and cognitive development such as those experienced by children with autism.

Eye contact

Overt visual attention, or the ability to direct our gaze to different parts of the environment around us, plays a critical role in intelligent behavior, from perception and learning to action and communication. We are developing systems and algorithms to help capture important information about human visual attention in a variety of settings, including systems for automatically detecting social gaze behaviors and non-invasive, real-world gaze measurement systems.