Research
My research explores how adaptive interfaces can reduce cognitive load for users across different ability levels. I lead the Adaptive Interfaces Lab at ETH Zürich, where our team of twelve researchers investigates real-time UI adaptation, gaze-driven interaction, and personalized information architecture.
Current projects include a system that dynamically adjusts interface complexity based on physiological stress indicators, and a framework for generating accessible alternatives to complex data visualizations.
Selected Publications
- "Adaptive Complexity Reduction in Data-Dense Interfaces" — CHI 2026, Best Paper Award
- "Gaze-Contingent UI Simplification for Cognitive Accessibility" — UIST 2025
- "Beyond WCAG: Personalized Accessibility Through Real-Time Adaptation" — ASSETS 2025
- "Measuring Cognitive Load in Enterprise Software" — IEEE TVCG, 2024
Teaching
I teach graduate courses on human-computer interaction and accessible design. My teaching philosophy centers on project-based learning — students work with real users and real constraints from day one.
Courses I currently teach:
- Advanced HCI — Research methods, prototyping, and evaluation
- Accessible Computing — Principles, standards, and emerging approaches
- Design Studio — Intensive hands-on design-build course with industry partners
The best interfaces don't just accommodate different users — they learn from them and evolve to meet them where they are.
Awards & Recognition
My work has been recognized with a CHI Best Paper Award (2026), an NSF CAREER Award (2024), and the ACM SIGCHI Outstanding Dissertation Award (2021). I serve on the program committees of CHI, UIST, and ASSETS.
Contact
I'm always interested in collaborations at the intersection of accessibility, adaptive systems, and real-world deployment. Reach out via email or connect with me on any of the platforms listed in the sidebar.