Eye-tracking for Intelligent Personalization of Information Visualization

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User-adaptive interaction, a field at the intersection of artificial intelligence (AI) and human-computer interaction (HCI), aims to create intelligent interactive systems that provide users with a personalized interaction experience by modelling and adapting in real-time to relevant users' needs and abilities. The benefits of user-adaptive interaction have been shown for a variety of tasks and applications (Jameson 2009). This proposal supports research at the forefront of this field by investigating a new domain of application for user-adaptive interaction: user-adaptive visualizations***Infovis is becoming increasingly important given the continuous growth of applications that allow users to view and manipulate complex data, not only in professional settings, but also for personal usage (e.g., monitoring fitness, tracking interactions in social media, understanding home resources consumption (Huang et al. 2015). To date, visualizations are typically designed based on the type of tasks and data to be handled, without taking into account user differences. However, there is mounting evidence that visualization effectiveness depends on a user's specific preferences, abilities, states, and even personality. The eye-tracking equipment requested in this proposal will be instrumental to investigate how to create visualizations that can infer the relevant user's characteristics from how users look at them, and personalized the visualization accordingly, to best suit the users needs and abilities. **