Jesús González will defend his thesis on Friday, November 28th

• The defence will take place at Sala Adela Moyua, Faculty of Science and Technology (EHU-Leioa) at 11:15

Jesús González Sieiro is an Energy engineer from the University of Vigo (2015-2019), with a master's degree in Industrial Mathematics from the University of Santiago de Compostela (2019-2021). Currently, a  PhD Student at the University of the Basque Country in collaboration with BCAM (2021-2025). Research interests focused on Computational Fluid Dynamics, Machine Learning, Deep Neural Networks, HPC, offshore wind engineering, aerodynamics, and optimal design. 

His thesis, titled “Enhancing CFD Simulations for Floating Offshore Wind Turbines Employing Deep Learning Techniques," is supervised by Prof. David Pardo (BCAM, Ikerbasque & UPV/EHU) & Dr. Vincenzo Nava (U. PoliTO). It is scheduled to be defended on November 28th, 2025, at Sala Adela Moyua, Faculty of Science and Technology (EHU - Leioa) at 11:15 a.m. 

On behalf of all members of BCAM, we would like to wish him all the best for the future, both professionally and personally.

Abstract

This dissertation proposes innovative Deep Learning (DL) methodologies to address the high computational cost and challenges associated with accurate Computational Fluid Dynamics (CFD) simulations, crucial for the design optimization of Floating Offshore Wind Turbines (FOWTs). The presented work is unified by the use of Automatic Differentiation (AD), which enables the integration of high-fidelity CFD codes into DL frameworks.