Giorgio Maria Cavallazzi

Overview

Currently at the first year of his Ph.D. program at City, University of London. The research topic consists in finding solutions to better understand and eventually control Turbulent Flows with Deep Learning techniques.

Previously, he obtained a B.Sc. in Aerospace Engineering and later a M.Sc. in Aeronautical Enigneering following the "Aerodynamics" exams track at Politecnico di Milano (PoliMi). He wrote his master thesis at the Karlsruhe Institutite of Technology with the Erasmus program, in which he took part in the devolopment of a Direct Numerical Simulation (DNS) code to evaluate the Drag Reduction of sinusoidal riblets in a turbulent channel flow.

Qualifications

• M.Sc. Aeronautical Engineering, Politecnico di Milano, Italy
• B.Sc Aerospace Engineering, Politecnico di Milano, Italy

Languages

English (can read, write, speak, understand spoken, peer review), Italian (can read, write, speak, understand spoken, peer review) and Spanish; Castilian (can read, understand spoken)

Title of thesis: Deep Learning for Reduced Order Modelling of Wall Bounded, Turbulent Flows

October 2022

Summary of research

The research topic consists in finding solutions to better understand and eventually control Turbulent Flows with Deep Learning techniques.

Research students

1^stsupervisor

• Professor Alfredo Pinelli, Professor of Fluid Simulation

2^ndsupervisor

• Dr Daniel Chicharro Raventos, Lecturer in Computer Science

Publications by category