Welcome to the research group on 
"Data-driven Nonlinear Mechanics" at KU Leuven

Our research focuses on the development of data-driven methodologies to model, control and design dynamic systems that are relevant to mechanical engineering. A recurrent subject of interest concerns the impact of nonlinearities on these systems. We address the full spectrum of topics in data-driven dynamics from test preparation, data acquisition and model construction to controller implementation and design optimisation. The originality of our work lies in a constant effort to apply to mechanical problems ideas and tools emerging in neighbouring fields, in particular in machine learning, control theory and nonlinear dynamics.

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We also teach at Bachelor and Master levels within the Faculty of Engineering Technology at KU Leuven. Our duties includes classes on mechanical vibrations, machine components, finite elements, and digital twins.

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We finally participate actively in the life and outreach of our scientific community. Every year, we attend conferences, visit labs, deliver research talks, review journal papers, co-organise short-courses, sessions and workshops, sit in doctoral committees, and provide consultancy services. Prof. Noël is also a member of the editorial board of the Mechanical Systems and Signal Processing journal.