Lorenzo Pareschi

Professore Ordinario

University of Ferrara

Italy

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Dr. Lorenzo Pareschi is a Professore Ordinario at Università degli Studi di Ferrara, Italy. His research focuses on statistical mechanics, optimization techniques, and modeling in complex systems, with recent contributions to epidemic modeling and kinetic theory. He has authored significant articles on the degree distribution of networks, polynomial approximations, and control strategies in magnetically confined fusion plasma.

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2022

Collaborators (5)

Andrea Medaglia

University of Oxford

UNITED KINGDOM

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Giuseppe Toscani

University of Pavia

ITALY

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ANDREA MIGNONE

Full Professor

University of Turin

ITALY

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Jonathan Franceschi

University of Ferrara

ITALY

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Mattia Zanella

Associate Professor

University of Pavia

ITALY

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Lorenzo Pareschi

Research Interests

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About

Articles (26)

Emerging properties of the degree distribution in large non-growing networks

A data augmentation strategy for deep neural networks with application to epidemic modelling

Conservative Polynomial Approximations and Applications to Fokker–Planck Equations

Instantaneous control strategies for magnetically confined fusion plasma

Kinetic description and convergence analysis of genetic algorithms for global optimization

A fourth-order accurate finite volume scheme for resistive relativistic MHD

Reduced Variance Random Batch Methods for Nonlocal PDEs

Micro-Macro Stochastic Galerkin Methods for Nonlinear Fokker–Planck Equations with Random Inputs

New trends on the systems approach to modeling SARS-CoV-2 pandemics in a globally connected planet

Optimization by linear kinetic equations and mean-field Langevin dynamics

Optimization by linear kinetic equations and mean-field Langevin dynamics

Gradient-Based Monte Carlo Methods for Relaxation Approximations of Hyperbolic Conservation Laws

Particle simulation methods for the Landau-Fokker-Planck equation with uncertain data

Modelling contagious viral dynamics: a kinetic approach based on mutual utility

New trends on the systems approach to modeling SARS-CoV-2 pandemics in a globally connected planet

An Adaptive Consensus Based Method for Multi-objective Optimization with Uniform Pareto Front Approximation

Multiscale Constitutive Framework of One-Dimensional Blood Flow Modeling: Asymptotic Limits and Numerical Methods

Constrained Consensus-Based Optimization

The Kinetic Theory of Mutation Rates

Modeling opinion polarization on social media

Effects of Vaccination Efficacy on Wealth Distribution in Kinetic Epidemic Models

Moment Preserving Fourier–Galerkin Spectral Methods and Application to the Boltzmann Equation

From agent-based models to the macroscopic description of fake-news spread: the role of competence in data-driven applications

Anisotropic Diffusion in Consensus-Based Optimization on the Sphere

Binary Interaction Methods for High Dimensional Global Optimization and Machine Learning

Spreading of fake news, competence and learning: kinetic modelling and numerical approximation

Collaborators (5)

Andrea Medaglia

Giuseppe Toscani

ANDREA MIGNONE

Jonathan Franceschi

Mattia Zanella

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