Davide Procacci

Davide Procacci is a Postdoctoral Researcher in the MultiphysX Flow Lab, Department of Engineering Mechanics at KTH Royal Institute of Technology, since March 2026.

His research combines scientific machine learning with computational fluid dynamics to accelerate and interpret the study of complex flows. As part of the Digital Futures-funded project, he develops neural operators as surrogate models for simulations of porous media flow, and uses convolutional neural networks and transformers for image enhancement and segmentation of experimental fuel cell imaging. In parallel, he studies the fundamental physics of turbulent multiphase flows, focusing on the interaction between wall turbulence and bubble-induced agitation and its effect on scalar transport.

He received his PhD in Chemical Engineering through a joint doctoral degree between NTNU (Norwegian University of Science and Technology) and TU Wien in 2026, under the supervision of Professor Jannike Solsvik at NTNU and Professor Alfredo Soldati at TU Wien, working on Direct Numerical Simulation of multiphase and turbulent flows.