RESEARCH
His research focuses on the development of software tools that support reproducible omics workflows and interactive web-based platforms for genomic data interpretation. These efforts aim to make complex bioinformatic analyses more accessible and usable for clinicians and biologists, thereby narrowing the gap between computational biology and its practical application in clinical and translational research.
In parallel, he focuses on enhancing deep learning models specifically designed for biological data, with an emphasis on improving performance, interpretability and usability. His work aims to integrate artificial intelligence with biology, using advanced computational methods to address complex biological and clinical questions. He is particularly interested in bridging these two domains to enable AI-driven solutions in biomedical research and healthcare.

BIOGRAPHY
Master’s and Bachelor’s degrees in Computer Engineering from the Public University of Navarre (UPNA), with specialization in Computing, Intelligent Systems, and Big Data.
Between 2017 and 2021, he was a Computer Engineer at Navarrabiomed’s Translational Bioinformatics Unit, where he contributed to the design and development of regional genomic (WGS and WES) infrastructures and pipelines for projects such as NAGEN. He also collaborated with NASERTIC to implement bioinformatic solutions supporting public health and research.
Since 2022, he has served as a Research Engineer at King Abdullah University of Science and Technology (KAUST), focusing on enhancing computational tools applied to biological data. His role includes building web applications for genomics, automating computational workflows, and supporting teaching activities in fundamental bioinformatics.