M.Sc. (Honors), University of Milan (1988); Research Staff Member, Dida*El Milan (1988-1989); Research Fellow, I.R.S.T. Istituto per la Ricerca Scientifica e Tecnologica (1989-1991); Research Programmer Carnegie Mellon University (1992); M.Sc., University of Pittsburgh (1995); Ph.D., University of Pittsburgh (1999); Assistant Professor, University of British Columbia (1999-2005), Associate Professor, University of British Columbia (2006 - 2016), Professor (2016); Distinguished Scholar, Sauder School of Business (2020)
My goal is to integrate research in Artificial Intelligence, Human Computer Interaction and Cognitive Science to make complex interactive systems increasingly more effective and adaptive to the users' needs. I am particularly interested in extending the range of user features that can be captured in and efficiently processed by a computational user model - from purely cognitive features (knowledge, goals, preferences), to meta-cognitive skills (e.g., the capability of effectively exploring a large information space), personality traits and emotional reactions. The aim is to widen the spectrum of information that an interactive system can use to dynamically adapt its behavior to a user's needs. My students and I are currently applying this research to: (1) generate adaptive visualizations [I]; (2) capture and adapt to a user's reasoning processes by using eye-gaze information [II] and decision-theoretic methods [IV]; (3) Provide adaptive support to interface customization [III]; (4) devising emotionally intelligent agents for educational games [V];
Conati C. and Merten C. (2007). Eye-Tracking for User Modeling in Exploratory Learning Environments: an Empirical Evaluation. Knowledge Based Systems, Volume 20 , Issue 6 (August 2007), Elsevier Elsevier Science Publishers B. V. Amsterdam, The Netherlands
Bunt A., Conati C. and McGrenere J. (2007). Supporting Interface Customization Using a Mixed-Initiative Approach. Proceedings of the 2007 International Conference on Intelliget User Interfaces, p. 92-101. Winner of the Best Paper Award.
Muldner K. and Conati C. (2007). Evaluating a Decision-Theoretic Approach to Tailored Example Selection. Proceedings of IJCAI 2007, 20th International Joint Conference in Artificial Intelligence, p. 483-488.
Conati C. (2002). Probabilistic Assessment of User's Emotions in Educational Games . Journal of Applied Artificial Intelligence, special issue on ? Merging Cognition and Affect in HCI?, vol. 16 (7-8), p. 555-575.
Conati C., Gertner A. and VanLehn K. (2002). Using Bayesian Networks to Manage Uncertainty in Student Modeling . Journal of User Modeling and User-Adapted Interaction, vol. 12(4), p. 371-417, Winner of the 2002 James Chen Annual Award for Best UMUAI Paper.