This research investigates cognitive diversity in software engineering. Through eye-tracking and think-aloud studies, it shows that engineers approach problems differently, while existing software tools often favour particular thinking styles. Designing more inclusive tools could improve performance, broaden participation in decision-making, and reduce unintended bias in the technologies we build.

This research exposes a hidden privacy risk in online voting and video conferencing: eye movements captured by standard webcams can reveal user choices. Using AI models, voting decisions were inferred with over 95% accuracy, highlighting that digital security must address behavioral signals—not just encryption.

This research investigates why children struggle to learn pronouns and why these difficulties vary across languages. Through cross-linguistic experiments and eye-tracking, it shows that pronouns pose an intrinsic processing challenge. Some languages compensate for this difficulty, offering new insights into language development and human learning.