Bioinformatics engineer working at the interface of artificial intelligence, genomics, epigenomics, and computational pathology.
Gabriel Cabas is a Bioinformatics Engineer working at the interface of artificial intelligence, genomics, epigenomics, and computational pathology. His work focuses on developing machine learning and deep learning approaches to extract biological insight from large-scale omics datasets and histological images.
He is particularly interested in genomic prediction, genome-wide association studies, polygenic risk modeling, and AI-driven analysis of tissue architecture. His research contributes to the development of data-driven tools for understanding complex disease mechanisms and advancing precision medicine in research and clinical settings.