My research is devoted to develop microscopic, macroscopic and multiscale models for describing and forecasting vehicular traffic on single roads and road networks. From the mathematical point of view, I use ODEs and (systems) of 1D hyperbolic PDEs, numerically approximated by Godunov method.
I have a special interest in the problem of comparing traffic states, like the ones coming from the solution of the models. To this end, I have investigated, from the numerical side, the use of Wasserstein distance instead of more classical L^p distances.
Collaborations with private companies allowed me to work with some real data sets coming from both mobile (GPS-based) and fixed sensors.


My research is devoted to develop microscopic, macroscopic and multiscale models for describing and forecasting pedestrian dynamics in built environments. From the mathematical point of view, I use 2D hyperbolic PDEs.
I have a special interest in the problem of steering crowds preserving at any time its natural behavior. This means that people are not asked or forced to follow a specific path, rather I want to control the environment or the path of some special agents in such a way that the observed behavior of the crowd is "naturally" optimal.


My research is devoted to the construction of optimal supports for unprintable objects. Using the level-set method, I "inflate" the object in such a way that overhangs disappear, thus finding, as a by-product, the minimal-volume support specifically conceived for the object.
More in general, I am interested in any kind of advanced mathematical method to solve problems related to low cost 3D printers based on the FDM technology.


I am interested in any kind of fast numerical method for solving the Hamilton-Jacobi-Bellman and Hamilton-Jacobi-Isaacs equations associated, respectively, to optimal control problems and differential games. In particular I worked on the extensions of the Dijkstra-inspired Fast Marching Method to Hamilton-Jacobi equations more general than the eikonal one.