RESEARCH GROUP @ UNIPV
We are a group of researchers working on challenging Mathematical Optimization problems using numerical methods based on Mathematical Programming, Machine Learning, and Artificial Intelligence.
We love to put optimization theory into practice while solving industrial applications.
We are passionate about new theoretical questions coming from real-life applications.
Computational Optimal Transport
Model and Algorithms for Kantorovich-Wasserstein distances, Wasserstein Barycenters, and Fourier-based metrics
Models and algorithms to deal with challenges arising from health service management and to support decisions under uncertainty
Traveling Salesman Problem, Graph Coloring, Stable Set, Total Matching, and Total Coloring
Interpretable Machine Learning
Development of Machine Learning techniques based on interpretable mathematical models that provide explainable outcomes
Robust Optimal Power Flow
Development of models and algorithms regarding the Optimal Power Flow problem in a stochastic setting that arises from Renewable Energy Sources