What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Mathematical analysis
- Artificial intelligence
His primary areas of study are Boltzmann equation, Mathematical analysis, Statistical physics, Spectral method and Numerical analysis.
His studies deal with areas such as Optimal control, Minification, Boltzmann constant, Euler equations and Discretization as well as Boltzmann equation.
His Mathematical analysis study typically links adjacent topics like Relaxation.
His Relaxation study combines topics in areas such as Partial differential equation and Applied mathematics.
His Statistical physics research is multidisciplinary, incorporating perspectives in Lattice Boltzmann methods, Kinetic theory of gases and Classical mechanics.
Lorenzo Pareschi has included themes like Fast Fourier transform, Collision operator, Fokker–Planck equation, Fourier series and Hard spheres in his Spectral method study.
His most cited work include:
- Implicit---Explicit Runge---Kutta Schemes and Applications to Hyperbolic Systems with Relaxation (396 citations)
- Numerical methods for kinetic equations (203 citations)
- On a Kinetic Model for a Simple Market Economy (180 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Applied mathematics, Boltzmann equation, Statistical physics, Mathematical analysis and Numerical analysis.
His Applied mathematics research is multidisciplinary, relying on both Optimal control, Uncertainty quantification, Linear multistep method, Mean free path and Discretization.
His Boltzmann equation research includes themes of Spectral method, Hard spheres and Boltzmann constant.
His research integrates issues of Distribution, Kinetic theory of gases and Nonlinear system in his study of Statistical physics.
His studies in Mathematical analysis integrate themes in fields like Relaxation and Relaxation.
His work in Numerical analysis addresses issues such as Partial differential equation, which are connected to fields such as Convection–diffusion equation.
He most often published in these fields:
- Applied mathematics (32.02%)
- Boltzmann equation (32.46%)
- Statistical physics (25.88%)
What were the highlights of his more recent work (between 2017-2021)?
- Applied mathematics (32.02%)
- Numerical analysis (22.81%)
- Statistical physics (25.88%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Applied mathematics, Numerical analysis, Statistical physics, Optimal control and Uncertainty quantification.
His research in Applied mathematics intersects with topics in Global optimization, Boltzmann equation, Field, Linear multistep method and Discretization.
The Boltzmann equation study combines topics in areas such as Spectral method, Perturbation and Boltzmann constant.
His work carried out in the field of Numerical analysis brings together such families of science as Space, High dimensionality, Partial differential equation and Limit.
Lorenzo Pareschi combines subjects such as Mathematical model and Kinetic theory of gases with his study of Statistical physics.
His work in Uncertainty quantification addresses subjects such as Computation, which are connected to disciplines such as Mathematical analysis and Mean free path.
Between 2017 and 2021, his most popular works were:
- Vehicular traffic, crowds, and swarms: From kinetic theory and multiscale methods to applications and research perspectives (83 citations)
- Structure Preserving Schemes for Nonlinear Fokker–Planck Equations and Applications (44 citations)
- Particle based gPC methods for mean-field models of swarming with uncertainty (28 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Mathematical analysis
- Artificial intelligence
Lorenzo Pareschi spends much of his time researching Applied mathematics, Kinetic equations, Model predictive control, Optimal control and Statistical physics.
His Applied mathematics research includes elements of Uncertainty quantification and Global optimization.
The concepts of his Model predictive control study are interwoven with issues in Control theory, Pareto index and Flocking.
His Optimal control research is multidisciplinary, incorporating elements of Uncertain data and Global strategy.
Lorenzo Pareschi integrates Statistical physics and Kuramoto model in his studies.
In his study, Mathematical analysis, Mean free path, Discretization and Distribution is strongly linked to Computation, which falls under the umbrella field of Convection–diffusion equation.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
