In the Developmental Intelligence Laboratory, our primary research aim is to understand human learning and early development. How do young children learn to see the world around them? How do they learn to talk? How do they learn to communicate and interact with others? To answer these questions, the primary approach in our research is to attach GoPro-like cameras on the head of young children to record egocentric video from their point of view. Using this innovative approach, we've been collecting video data of children’s everyday activities, such as playing with their parents and their peers, reading books with parents and caregivers, and playing outside. We've been developing and employing state-of-the-art machine learning and data mining approaches to analyze high-density behavioral data. This research line will ultimately solve the mystery on why human children are such efficient learners. Moreover, the findings from our research will be used to help improve learning of children with developmental deficits. A complimentary research line is to explore how human learning can teach us about how machines can learn. Can we model and simulate how a human child learns and develops? To this end, our research aims at bridging and connecting developmental science in psychology and machine learning and computer vision in computer science.
University of Texas - Austin | Department of
Lab email: email@example.com | Address: 108 E Dean Keeton St, Austin, TX 78712
Designed by Andrei Amatuni, Yayun Zhang, Dian Zhi