Hello, my name is Lorenzo Campoli and I'm currently working at The University of Melbourne on data driven turbulence modeling. At the moment, I am exploring the possibility of using unsupervised machine learning algorithms coupled with GEne Expression Programming (GEP) framework to improve the generalizability and explainability of Reynolds Averaged Navier-Stokes (RANS) turbulence closure models.

Previously, I was Assistant Professor at the Fluid Mechanics Department at Saint Petersburg State University. I worked on the development and implementation of numerical methods for high-speed non-equilibrium viscous reactive flows adopting a state-to-state and multi-temperature formulations. During this time, I also lead several courses about machine learning and hypersonics.

My scientific interests are related to hypersonic reactive viscous non-equilibrium flows, numerical methods for high-speed flows, shock-fitting, turbulence closure modeling, machine learning and high performance computing. I also collaborate to the UnDiFi-2D project about shock-fitting.