Sayeed Safayet Alam
School of Computing and Information Sciences
Sayeed Safayet Alam is a Ph.D. candidate at Florida International University. He is a member of the FIU VizLab where he works under the supervision of Dr. Radu Jianu Since 2013. He received B.Sc. in Computer Science and Engineering in 2009 from Bangladesh University of Engineering and Technology. His current research interests are in applications of eye-tracking to data visualization, and visual analytics.
Eye-tracking devices can tell us where on the screen a person is looking. Researchers generally analyze eye-tracking data manually, by examining every frame of a visual stimulus used in an eye-tracking experiment so as to match 2D screen-coordinates provided by the eye-tracker to relevant objects and content within the stimulus. This requires significant manual effort and is not feasible for analyzing data collected from many users, long experimental sessions, and heavily interactive and dynamic visual stimuli. In this dissertation, we propose a novel analysis method. We would instrument visualizations that have accessible open source-code, and leverage real-time information about the layout of the rendered visual-content, to automatically relate gaze-samples to visual objects drawn on the screen. Since such visual objects shown in a visualization generally stand for data, the method would allow us to essentially detect data that users focus on, or Data of Interest (DOI). Our research would result in two contributions. First, we aim to investigate the feasibility of collecting DOI data for real life visualization in a reliable way. As we will show, this is not self-evident. Second, we aim to formalize the process of collecting and interpreting DOI data and test whether the automated DOI detection can lead to research workflows, and insights not possible with traditional, manual approaches.