Mathieu Chollet

Laboratoire des Sciences du Numérique de Nantes, University of Glasgow

Papers

Total Citations

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About

Mathieu Chollet is a leading researcher at the intersection of human factors, robotics, and multimodal data analysis, with a primary focus on enhancing human performance and well-being in high-stakes environments. His work centers on two key areas: assessing cognitive states like situation awareness (SA) in robotic surgery, and modeling fatigue in human-robot collaborative work for Industry 5.0. Chollet’s major contribution lies in developing predictive models that leverage multimodal data—such as physiological signals and behavioral metrics—to objectively assess non-technical skills. For instance, his 2020 study on SA during robotic surgery (11 citations) pioneered a data-driven approach to replace subjective questionnaires, addressing how robotic systems disrupt team dynamics. Similarly, his 2024 work on fatigue modeling (10 citations) proposes system-level improvements for Operator 5.0, prioritizing worker wellbeing in digital factories. Though early in his career, Chollet’s research has already shaped discussions on human-centered automation, with his 2021 follow-up on predicting surgeon SA (2 citations) extending these methods. His work is notable for bridging cognitive science and engineering, offering practical tools to optimize human-robot teamwork in surgery and manufacturing.