TD
Thibault Dairay
Michelin
Scientific Computing Expert
Description
Thibault is deeply passionate about navigating through diverse scientific and technical domains alongside R&D collaborators. His journey spans from understanding physical principles to their mathematical representations, and from traditional numerical techniques to cutting-edge machine learning algorithms. He firmly believes that true innovation arises from the synergy of multidisciplinary teams, comprising individuals with varied expertise, ranging from highly specialized professionals to practical end-users. His immersion into scientific computing began in 2010, during his doctoral research, where he implemented advanced numerical methods for simulating turbulent flows. Subsequently, he spent four years in academia, contributing to projects at institutions such as Imperial College London and Ecole Centrale de Lyon, focusing on modeling and simulation of turbulent flows. At Michelin since 2017, Thibault is working on subjects linked to several aspects of applied mathematics and numerical methods (modelling, optimization and control). His primary focus lies in the development of hybrid methodologies that bridge the gap between physics-based models and data-driven approaches. He firmly advocates for leveraging external knowledge sources, including the vibrant open-source community, recognizing their potential to enhance Michelin's simulation tools and methodologies. In his role, he leads academic and industrial partnerships to address the forthcoming challenges in Michelin's simulation initiatives.
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