I am an Aeronautical Engineer, graduated from Universidad Politécnica de Madrid (UPM) in Madrid, Spain. My passion for numerical methods and computational fluid dynamics (CFD) began during my bachelor’s studies, where I developed a code to simulate ice accretion over aerodynamic surfaces. This project was in collaboration with the Applied Mathematics to Aerospace Engineering department at ETSIAE, UPM.

I furthered my expertise by completing my Master’s Thesis at KTH Royal Institute of Technology in Stockholm, Sweden, where I conducted a CFD study on a rocket jet impinging on a surface. Currently, I work as a Researcher in CFD at UPM, addressing various challenges in hydrodynamics, aerodynamics, and heat transfer for multiple companies. Alongside my professional work, I am pursuing a PhD focused on enhancing turbulence models using Machine Learning tools.

My enthusiasm for Fluid Mechanics and the complexities of its numerical modeling drives my research and teaching. The fascinating field of Machine Learning is revolutionizing progress and enabling groundbreaking discoveries, and I am excited to share my knowledge from a unique perspective that combines CFD and Machine Learning.

Navalapp provides a wonderful platform to achieve this goal, aligning perfectly with my passion for teaching and innovation in these fields.