The Scientific Machine learning and Advanced Reduction Techniques Laboratory (SMARTLab) deals with the development of advanced mathematical techniques for the solution of computational physics problems in industrial, environmental and biomedical engineering. Some of the specific research topics include:

• Scientific Machine Learning where machine learning is combined with physics based modelling.
• Development of intrusive (POD-Galerkin and reduced basis) and non-intrusive (DMD, POD-NN, etc) model reduction techniques.
• Numerical approximation of partial differential equations using finite elements and finite volume methods. 
• Computational fluid dynamics in the fields of industrial, environmental and biomedical engineering. 
• Inverse problems, Uncertainty Quantification and Optimization.

The SMARTLAB received funding thanks to a Starting Grant from the European Research Council (ERC) under the Horizon Europe 2023 program of the European Union (project DANTE, GA:101115741).