Geometric, Statistical and Numerical Method for Data Science

Faculty Staff

B. Iannazzo, Head (Numerical Analysis)
D. Burini (Mathematical Physics)
A. Capotorti (Applied Probability and Statistics)
N. Ciccoli (Geometry)
I. Gerace (Numerical Analysis)
A. Troiani (Applied Probability and Statistics)

The aim of the group is the design and analysis of algorithms for "data science" problems from an interdisciplinary perspective.
Our methodology spans from linear algebra to optimization, from statistics to uncertainty quantification, and from algebra to algebraic topology.
We emphasize finding and using hidden structures within data. Examples include using homology to study complex networks and optimization on differentiable manifolds to compute statistical quantities. We pay special attention to machine learning models.