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Highlight-Informed Saliency Model (HISM) for GUI Design
This project explores how dynamic visual highlights influence user attention in graphical user interfaces (GUIs). Using eye-tracking data, we analyzed temporal changes in gaze behavior across free-viewing and task-driven scenarios. Our novel Highlight-Informed Saliency Model (HISM) integrates spatial and temporal data to predict attention shifts over time, outperforming existing models. These insights enable the design of more effective and user-focused GUIs.
RelEYEance: Real-Time Gaze-Based AI Reliance Detection
This project introduces the RelEYEance model for detecting user reliance on AI in real-time. Leveraging eye-tracking data, we developed a clustering pipeline to classify user reliance into over-reliance, under-reliance, and appropriate reliance during a time-sensitive monitoring task. The model enables adaptive interventions for recalibrating reliance.
Influence of Work Motivation and Task Difficulty on Human Reliability.
Published in Proceedings of the 2nd International Conference on Reliability Systems Engineering (ICRSE 2017), Beijing, 2017, 2017