Visual scan path analysis using eye tracking data Ziho Kang Industrial and Systems Engineering

Research focus Current application Characterizing eye tracking data through data analysis algorithms. E.g. Visual scanning sequence comparison methods, or clustering methods. Evaluating human performance. E.g. Whether individuals were interrogating aircraft pairs (or groups) that would collide. Using eye tracking data as a learning method. E.g. Using experts’ eye tracking data to teach the novices. Current application Air traffic management (collaborating with FAA Civil Aerospace Medical Institute)

Collaboration opportunities through eye tracking research Develop (full) automation methods for data analysis and visualization: E.g. Characterizing complex scan paths. Develop effective methods on human performance analysis: E.g. Workload. Apply eye tracking research in different research areas: E.g. Healthcare (autism), Education (reading), Weather system (forecasting). Develop mixed methods approach: E.g. Brain wave data, key input data, verbal/written reports. Available resources State-of-the-art eye tracker(s) to be purchased with the sampling rate at 250-500 hz.

Relevant publications in eye tracking research Design concepts and algorithms Z. Kang & S. J. Landry. (2015). An eye movement analysis algorithm for a multi-element target tracking task: Maximum transition- based agglomerative hierarchical clustering. IEEE Transactions on Human-Machine Systems, 45(1), 13-24. Z. Kang & E. J. Bass. (2014). Supporting the eye tracking analysis of multiple moving targets: Design concept and algorithm. In Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics (pp. 3191-3196), San Diego, CA. Understanding and utilizing cognitive processes Z. Kang & S. J. Landry. (2014). Using scanpaths as a learning method for a conflict detection task of multiple target tracking. Human Factors: The Journal of Human Factors and Ergonomics Society, 56 (6), 1150-1162. Z. Kang, E. J. Bass, & D. W. Lee. (2014). Air traffic controllers’ visual scanning, aircraft selection, and comparison strategies in support of conflict detection. In Proceedings of the 58th Annual meeting of the Human Factors and Ergonomics Society (pp. 77-81), Chicago, Illinois. Z. Kang & S. J. Landry. (2010). Capturing and analyzing visual groupings of multiple moving targets in an aircraft conflict detection task using eye movements. In Proceedings of the 54th Annual meeting of the Human Factors and Ergonomics Society (pp. 1906- 1910). San Francisco, CA.