We aim to significantly improve the Web user experience by leveraging eye gaze .
Our user study shows that user experience and traditional page load metrics are not well-correlated. To this end, we design WebGaze, a system that leverages user's eye gaze to systematically improve Web user experience. See the effect of WebGaze here.
We are now working on: (1) Scalably measuring user experience, (2) Defining a user's perceived page load time implicitly using their eye gaze, (3) Building saliency models for WebGaze, and (4) Designing new optimizations that account for both user interest and the underlying network infrastructure.
Work on characterizing and modeling user-centered load times for mobile Web pages accepted to MobileHCI 2020!
Work on classifying reading comprehension of Web news articles accepted at ETRA 2020!
Work on realtime reading detection with applications to the Web accepted at ETRA 2019!