CNR-INM Multidisciplinary Analysis & Optimization Research Group
The CNR-INM Multidisciplinary Analysis & Optimization Research Group (MAO) develops computational methods for simulation-based design optimization, surrogate modelling, dimensionality reduction, and machine learning for engineering applications.
Research activities focus on numerical and data-driven approaches for the analysis and design of complex systems, with applications in marine hydrodynamics, aerodynamics, and multidisciplinary engineering design.
This community collects datasets, software, and research outputs produced by the group and its collaborators. It includes benchmark datasets for simulation-based design optimization and dimensionality reduction methods, such as the PME benchmark datasets for gliders, airfoils, ships, and propellers, as well as open-source tools and reproducible research artifacts supporting computational engineering and design optimization studies.
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