Artificial Intelligence technologies are undoubtedly making human life easier over the last years. In particular, machine learning based systems are reaching society at large and in many aspects of the everyday life and the professional world. Yet with its benefits, machine learning techniques are not absolutely objective since model classifications and predictions rely heavily on potentially biased data.

Energy engineer by the University of Vigo (2015-2019), with a master degree in Industrial Mathematics by the University of Santiago de Compostela (2019-2021). Currently, Phd student at University of Basque Country in collaboration with BCAM. Research interests focused on computacional fluid dynamics, machine learning, HPC, offshore wind engineering, aerodynamics and optimal design.

PhD Student at BCAM

PhD Student at BCAM

PhD Student at BCAM. 

Research Fellow at the Computational and Applied Statistics group.
Data Science Coordinator at the Knowledge Transfer Unit (KTU).

Short bio:

I received a degree in Mathematics from the University of the Basque Country (UPV/EHU) in 2014. During 2014-2016, I did a master degree in Mathematical Engineering at Complutense University of Madrid (UCM). Currently, in the Heuristic Optimization group of BCAM since November 2019: as research Technician at first and as PhD student since August 2021. My doctoral thesis project studies the potential of mathematical modeling and optimization as a support tool in the decision-making process of Emergency Healthcare Systems.

PhD Student at BCAM

BCAM-TECNALIA PostDoc Fellow

I work in Singularity Theory and Algebraic Geometry. I am interested in singular spaces and maps. I have worked in arc spaces, normal surface singularities, geometry of degenerating families, intersection cohomology, Hodge theory and related techniques, Lipschitz geometry, characteristic classes of singular spaces, invariants coming from symplectic topology and in other aspects of geometry and topology of algebraic varieties.
 

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