About
I am a PhD Candidate in Computational Physics at the Polytechnic University of Catalonia and a visiting Researcher at the University of Tokyo. My research focuses on Computational Materials Science, where I use first-principles atomistic modeling and machine learning techniques, such as Density Functional Theory, Machine Learning Interatomic Potentials, and Graph Neural Networks, to understand the physics and chemistry of materials. I am also interested in developing responsible AI tools to accelerate materials discovery and property prediction.
My current research primarily revolves around two topics. First, I am deeply interested in how temperature influences the optoelectronic properties of semiconductors, and my second main interest lies in the creation of high-quality datasets for training machine learning models in materials science. In addition, my research experience spans various topics, including computational characterization of materials for energy applications, machine learning-based crystal structure prediction, and the study of phase competition in systems with multiple metastable states.
Throughout my brief research career, I have worked in leading institutions across Spain, the United Kingdom, and Japan, collaborating in highly international and intellectually stimulating environments. I have presented my work at major international conferences, such as MRS (USA), EMRS (France), and AI4X (Singapore), and have authored and co-authored publications in high-impact journals, such as the Journal of the American Chemical Society.
