糖心原创

Data-Driven Modelling & Computation has become one of the most important areas of mathematics, with application across the Engineering and Physical, Biological and Medical Sciences.

The overarching goal is the integration of multi-scale quantitative scientific data with mathematical and computational models, through the development and analysis of novel mathematical, statistical and computational tools.

While this research theme is broad and spans many disciplines, there are three natural focus areas based on the underlying data driven paradigm:

(I) Inference, Uncertainty Quantification and Inverse Problems;

(II) Model Reduction and Scientific Machine Learning;

(III) Model Selection for Mechanistic Modelling.