AI-Driven Personalization to Support Human-AI Collaboration

Speaker: Dr. Cristina Conati, University of British Columbia

Abstract: At the Human-AI Interaction group at the University of British Columbia, we investigate how to support Human-AI collaboration via AI artifacts that can understand relevant properties of their users (e.g., states, skills, needs) and personalize the interaction accordingly in a manner that preserves transparency, user control and trust. In this talk, I will illustrate examples of our research in AI-driven personalization spanning areas such as  Intelligent Tutoring Systems,  User Adaptive Visualizations and  Explainable AI.  

Biography: 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, and an M.Sc. and Ph.D. in Intelligent Systems at the University of Pittsburgh. Cristina has been researching human-centered AI and AI-driven personalization for over 25 years, with contributions in the areas of  Information Visualization, Intelligent Tutoring Systems, User Modeling, Affective Computing,and Explainable AI. Cristina's research has received 10 Best Paper Awards and  the Test of Time Time Award  2022 from the Educational Sata Mining Society. She is a Fellow of AAAI (Association for the Advancement of AI) and of ACM   (Association for Computing Machinery), and co-Editor in Chief of the Journal of AI in Education. She served as President of AAAC, (Association for the Advancement of Affective Computing), as well as Program or Conference Chair for several international conferences.

Host: Prof. Monica Landoni