Development of a data-driven wall-model for separated flows (Keynote Lecture)
Margaux Boxho, Michel Rasquin, Thomas Toulorge, Grégory Dergham, Grégoire Winckelmans and Koen Hillewaert

Effects of uncertainties of image-based material properties of great vessels on vascular deformation
Benigno Marco Fanni, Maria Nicole Antonuccio, Giuseppe Santoro, Alessandro Mariotti, Maria Vittoria Salvetti and Simona Celi

Quantifying Uncertainties in Direct Numerical Simulations of a Turbulent Channel Flow
Joseph O‘Connor, Sylvain Laizet, Andrew Wynn, Jon McCullough and Peter Coveney

Quantification of time-averaging uncertainties in turbulence simulations
Donnatella Xavier, Saleh Rezaeiravesh, Ricardo Vinuesa and Philipp Schlatter

Data-Driven Inference Design for the Bayesian Uncertainty Quantification of the Reactive Shock-Bubble Interaction
Ludger Paehler and Nikolaus A. Adams

Multi-Fidelity Surrogate Models for Aerodynamic Applications
Andrew Mole, Alex Skillen and Alistair Revell

Energy consistent machine learning closure model for fluid flow problems
Toby van Gastelen and Benjamin Sanderse

Data-driven LES for the flow around a 5:1 ractangular cylinder
Gabriel I. Moldovan, Alessandro Mariotti, Guilaume Lehnasch, Laurent Cordier, Maria V. Salvetti and Marcello Meldi

Adaptive Gaussian process surrogate modelling of large-eddy simulation for microscale atmospheric dispersion
Bastien X. Nony, Mélanie C. Rochoux, Didier Lucor and Thomas Jaravel

Learning reduced subgrid-scale models
Wouter Edeling and Daan Crommelin

Explorative In-situ Analysis of Turbulent Flow Data Based on a Data-Driven Approach
Christian Gscheidle and Jochen Garcke