Kolloquium Laura Maria Sangalli: Physics-Informed Spatial and Functional Data Analysis over non-Euclidean Domains

By Laura Maria Sangalli, MOX – Dipartimento di Matematica, Politecnico di Milano, Italy

Recent years have seen an explosive growth in the recording of increasingly complex and high-dimensional data, whose analysis calls for the definition of new methods, merging ideas and approaches from statistics and applied mathematics. My talk will focus on spatial and functional data observed over non-Euclidean domains, such as linear networks, two-dimensional Riemannian manifolds and non-convex volumes. I will present an innovative class of methods, based on regularizing terms involving Partial Differential Equations (PDEs), defined over the complex domains being considered. These Physics-Informed statistical learning methods enable the inclusion of the available problem specific information, suitably encoded in the regularizing PDE. Illustrative applications from environmental and life sciences will be presented.

Short CV:

Please see: Laura Sangalli – short CV

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