معرفی
Cristina Conati is a Professor at the University of British Columbia, Canada, with an extensive research portfolio spanning artificial intelligence, human-computer interaction, and educational technology. Her work focuses on developing intelligent systems that adapt to user characteristics and behaviors, particularly through the analysis of eye-tracking data and other implicit user signals.
Her research interests include user-adaptive visualizations, intelligent tutoring systems, explainable AI, and eye-tracking analysis. She investigates how AI can be used to personalize user experiences, particularly in educational contexts, by modeling user cognitive abilities, emotional states, and learning behaviors. Her work often bridges theoretical AI research with practical applications in education and decision support.
Analysis of her recent publications (2023-2025) shows a strong focus on explainable AI in educational contexts, adaptive visualization techniques, and the use of eye-tracking to understand and support user interactions. Her research demonstrates a consistent trajectory toward making AI systems more transparent, adaptive, and effective for diverse users across various domains including education, healthcare, and decision-making.
- Extensive work on user modeling through eye-tracking data
- Development of adaptive visualization techniques
- Research on explainable AI for educational applications
- Studies on how individual differences affect user-system interaction
Her research has significant implications for designing more effective educational technologies, decision support systems, and user interfaces that can adapt to individual user needs and characteristics. She has been instrumental in advancing the field of user-adaptive interfaces through both theoretical contributions and practical implementations.
