I completed my Master’s in AI and Robotics at the University of Hertfordshire, where I worked on artificial life, HCI, and affective robotics. Before joining UNIL, I focused on low-cost assistive technologies for disadvantaged groups. That work grew out of a question that still drives me now: how can we design systems that support people without making them more dependent on technology?
I have since completed my PhD thesis, which examined reflexivity in the age of AI: the ability to sort through information, question experience, and make one’s own judgments rather than simply accept what a system provides.
My current research focuses on cost effective technologies that support executive functioning and working memory for people facing cognitive, situational, or structural constraints. More broadly, I study how intelligent systems can help people without taking too much out of their hands.
A central theme in my work is what I call cognitive durability: designing AI-supported systems that help people remain capable over time. I am particularly interested in hybrid forms of interaction, intentional latency, and mixed-intelligence approaches that make room for reflection and help preserve competence.
For me, HCI is where some of the most urgent questions about AI now sit, especially as these systems become part of everyday life.
Doctoral Thesis:
Adaptive Supports for Self-Reflection: Designing and Evaluating Hybrid Tools for Reflective Practice (2025)
Publications:
Tyler, J., Boldi, M.-O., & Cherubini, M. (2022). Contemporary self-reflective practices: A large-scale survey. Acta Psychologica, 230, 103768. https://doi.org/10.1016/j.actpsy.2022.103768
Arnéra, J., Chan, M., & Cherubini, M. 2024. Digital, Analog, or Hybrid: Comparing Strategies to Support Self-Reflection. In Proceedings of the 2024 ACM Designing Interactive Systems Conference (DIS ’24). Association for Computing Machinery, New York, NY, USA, 3435–3452. https://doi.org/10.1145/3643834.3661558