Sayeed Safayet Alam

Florida International University

Lecture Information:
  • May 12, 2017
  • 11:00 AM
  • ECS 349

Speaker Bio

Sayeed Safayet Alam is a Ph.D. candidate at Florida International University. He is a member of the FIU VizLab where he worked under the supervision of Dr. Radu Jianu from 2013 to 2016. Since then Sayeed has been working under the supervision of Dr. S. S. Iyengar.  He received B.Sc. in Computer Science and Engineering in 2009 from Bangladesh University of Engineering and Technology. His 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 frequently 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 related objects and content within the stimulus. Such task 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 contribute a novel analysis method. We would instrument visualizations that have 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 are shown in a visualization stand for data, the method would allow us to necessarily detect data that users focus on or Data of Interest (DOI). Our research would result in two contributions. First, we demonstrated 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 formalized 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.