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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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