The UN-BIASED project (UNcertainty quantification and modelling Bias Inhibition by means of an Agnostic Synergist Exploitation of multi-fidelity Data) aims at developing an innovative Scientific Modelling paradigm capable of mitigating potential cognitive biases affecting the modelling process, with particular focus on Aerospace engineering applications.

Giulio Gori short bio

"I was awarded a PhD in Aerospace Engineering in January 2019, from Politecnico di Milano, with a thesis focused on developing numerical methods and computational tools for renewable energy applications. Then, I moved to INRIA, the French national lab for research in informatics and automatics, and to the CMAP (Centre de Mathématiques Appliquées) at Ecole Polytechnique in Paris, to work on uncertainty quantification. In 2021, I re-joined Politecnico di Milano and now I am a Researcher @DAER. My fields of interest cover many applications in the field of space and aeronautical engineering including in-flight icing, turbomachinery, thermodynamic and fluid dynamics modeling, Bayesian inference, uncertainty quantification and robust optimization."