2:30 p.m.
Luca Calatroni Università di Genova
Computational imaging and learning: from physical modelling to data-driven approaches.
This talk presents recent advances at the intersection of computational imaging and machine learning, illustrating how physical models and data-driven approaches can be combined to address complex inverse problems. Through applications in biomedical imaging, microscopy, and cultural heritage reconstruction, we will show how computational mathematics contributes to building reliable, interpretable, and efficient learning-based methods. Emphasis will be placed on model-based regularization, optimization techniques, and physics-informed learning as key tools for designing robust and principled imaging algorithms.
3:45 p.m.
Alessandro Lanza
Variational Methods for Image Analysis
Many image processing problems are inverse ill-posed problems, which can be usefully cast in variational form: the sought-for image is obtained as the solution to a suitably designed optimization problem encoding information on the acquisition process and the target. In this talk, we'll introduce the basics of variational methods and explore their diverse applications in image analysis. We'll then delve into the specific research themes our group is currently pursuing in this exciting and evolving field.
4:05 p.m.
Marco Boschetti
Matheuristics: using Mathematics for heuristic design
Matheuristics are heuristic algorithms based on mathematical tools such as the ones provided by mathematical programming, that are structurally general enough to be applied to different problems with little adaptations to their abstract structure. The focus will be on their application to real-world problems, particularly in the context of prescriptive analytics.
4:25 p.m.
Carolina Beccari
Computational Geometric modeling
Geometric modeling focuses on using computational methods to describe and study shapes, with applications ranging from Computer Aided Design and computer graphics to 3D printing and biomedical simulations. The talk will cover essential ideas, present ongoing research, and offer an overview of a field rich in mathematical and interdisciplinary challenges.
4:45 a.m
Caterina Tamburini Optit
Digital Innovation per l'Industria: il Ruolo della Decision Science
La presentazione esplorerà come la Decision Science agisca da motore per l'innovazione digitale, guidando le aziende verso l'eccellenza operativa.
L'intervento si concentrerà su come la modellazione matematica possa essere impiegata per formulare e risolvere problemi decisionali complessi, contribuendo a trasformare processi oggi manuali in processi integrati ed automatizzati.
Saranno inoltre evidenziate le sfide e le strategie per integrare questi approcci "Smart" con i sistemi esistenti, portando esempi di applicazioni reali in settori come l'Energia e la Logistica.
5:05 p.m.
Claudio Gambetti Onit
TBA
5:25 p.m.
Lucrezia Vernia CyberTec
Mathematics for reliable, secure, meaningful data.
5:45 p.m.
Antonella Guidazzoli CINECA
TBA