Eye-tracking has been extensively used both in psychology for understanding various aspects of human cognition, as well as in human computer interaction (HCI) for evaluation of interface design or as a form of direct input. In recent years, eye-tracking has also been investigated as a source of information for machine learning models that predict relevant user states and traits (e.g., attention, confusion, learning, perceptual abilities). These predictions can then be leveraged by AI agents to personalize the interaction with their users. In this talk, I will provide an overview of the research my lab has done in this area, including predicting user cognitive skills, and affective states, with applications to User-Adaptive Visualizations and Intelligent Tutoring Systems.
Dr. Conati is a Professor of Computer Science at the University of British Columbia, Vancouver, Canada. She received an M.Sc. in Computer Science at the University of Milan, as well as an M.Sc. and Ph.D. in Intelligent Systems at the University of Pittsburgh. Conati’s research is at the intersection of Artificial Intelligence (AI), Human Computer Interaction (HCI) and Cognitive Science, with the goal to create intelligent interactive systems that can capture relevant user’s properties (states, skills, needs) and personalize the interaction accordingly. Conati has over 100 peer-reviewed publications in this field and her research has received awards from a variety of venues, including UMUAI, the Journal of User Modeling and User Adapted Interaction (2002), the ACM International Conference on Intelligent User Interfaces (IUI 2007), the International Conference of User Modeling,…
March 04, 2020 at 5:45pm
Italian Cultural Centre – Museum & Art Gallery – Room 5 – 3075 Slocan St, Vancouver, BC, V5M 3E4