Started on April 1st, 2024, the DREAM project will deal with the mathematical and computational setting of accurate and efficient reduced order models for the numerical approximation of systems governed by parametrized partial differential equations in real-time. Foreseen methodologies will leverage the accuracy of physics-based techniques and the versatility of data-driven methods based on neural networks. These strategies are motivated by several applications in Engineering, ranging from the simulation-assisted design & calibration of micro-electro-mechanical systems, to the optimal transport of nano-particle swarms in personalized medicine. These are just two examples of problems where, besides numerical approximation, efficient strategies are required to handle PDE-constrained optimization and uncertainty quantification problems.
Funded with 1 M€, the DREAM project is one of the 9 starting grants awarded at the national level, out of 462 submitted proposals, in the Physical Sciences and Engineering (PE) macrosector. Hosted by Politecnico di Milano, DREAM will last for 5 years and will involve a (dream) team of PhD students, Postdoctoral Fellows, and Young Researchers at the forefront in Computational Sciences and Engineering.
More information on the results of the FIS Call: https://www.mur.gov.it/it/news/lunedi-31072023/ricerca-47-le-proposte-deccellenza-selezionate-il-fondo-italiano-la-scienza