We present a novel computational framework for portfolio-wide risk management problems where the presence of a potentially large number of risk factors makes traditional numerical techniques ineffecti...
Lax-Wendroff methods for linear systems of conservation laws are based on Taylor expansions in time in which the time derivatives are transformed into spatial derivatives using the governing equations...
Low Mach problems arise in gas dynamics when the local speed is much smaller than the acoustic waves. In these regimes, a full resolution of all the waves requires very small time steps, while usually...
In this talk I will investigate the theoretical and numerical properties of the first-order Lighthill-Whitham-Richards (LWR) traffic flow model with time delay. Since standard results from the literat...
Nonlinear differential matrix equations generally stem from the semi-discretization on a rectangular grid of nonlinear partial differential equations (PDEs). The two main challenges related to approxi...
Advection-diffusion-reaction equations have a moltitudine of applications, such as in climate, water and air quality models, or in short and medium range weather forecasting. Due to the potentially ve...
In this talk, we present the construction of PDE model describing the evolution of microalgae or bacteria interacting together and in interaction with their environment. These models are based on the ...
The aim of this talk is to introduce a method to estimate the production of ozone due to vehicular traffic. The traffic flow is modeled via the second-order Collapsed Generalized Aw-Rascle-Zhang model...
The broad research thematic of flows on networks was addressed in recent years by many researchers, in the area of applied mathematics, with new models based on partial differential equations. The lat...
The classical Dynamic Programming (DP) approach to optimal control problems is based on the characterization of the value function as the unique viscosity solution of a Hamilton-Jacobi-Bellman (HJB) e...
In this talk I will present a data-driven iteratively regularized Landweber iteration for solving linear and nonlinear ill-posed inverse problems. The method takes into account training data, which ar...
