A team of U of T computer scientists explores how an interactive camera robot can assist in creating dynamic tutorial videos based on subtle verbal and non-verbal instructor cues.
New research on training decision-making AI reveals insights into normative judgments
Transforming education through AI-powered adaptive experiments: U of T computer scientists’ team wins XPRIZE Digital Learning Challenge
U of T receives $200-million grant to support Acceleration Consortium's ‘self-driving labs’ research
U of T computer scientists' MOOClet framework helps personalize and improve online learning experiences
The Adaptive Experimentation Accelerator, which includes Assistant Professor Joseph Jay Williams and U of T CS students Ilya Musabirov, Mohi Reza, Pan Chen and Harsh Kumar, is one of three finalists for the XPRIZE Digital Learning Challenge. The team’s software architecture uses machine learning to design inclusive and personalized online classrooms.










