Host: TUe (NL)
Main supervisor: Dr. Amritam Das (TUe, NL) Co-supervisors/mentors: Prof.dr.ir. Roland Toth (TUe, NL), Prof.dr.ir Tim Claeys (KUL, BE), Ir. Rob Kleihorst (Philips, NL)
Duration: 36 months
Required profile: Electrical Engineering Desirable skills/interests: Machine Learning, Data-driven modelling, Control design, Electromagnetism
Objectives: Modelling EMC is challenging due to nonlinear behavior, frequency-dependent interactions, complex geometries and many uncertainties involved. Current technqiues are heavily limited due computational burden and are often too costly to enable optimization early in the design process. This DC will aim to capture the time-varying behaviour of components, connectivity, and operational conditions with machine learning methods, such as Physics-guided Neural Networks (PGNNs) and explore control strategies to design controllers efficiently based on the learnt models to suppress electromagnetic interference within electronic systems. The DC will also support capturing time-varying behavior of EMC and contribute to the desing of a medical collaborative system.
Secondments (2-4 months in total): KU Leuven (BE), Philips (NL)