Summary
Raquel Dias is an assistant professor and computational biologist with 12 years of experience applying machine learning and deep learning to genomic, transcriptomic, and structural biology problems. Her work spans protein folding and protein–ligand interaction modeling, genomic imputation for GWAS, and uncovering genetic risk factors in underrepresented populations, notably identifying prostate cancer risk alleles prevalent in Native American communities. Trained as a biologist with advanced computational degrees, she bridges experimental validation and AI-driven modeling to pinpoint how mutations affect protein stability and disease mechanisms. At Scripps she led translational bioinformatics projects and developed AI tools to improve preprocessing and interpretation of genomic data, and she continues to push those methods toward clinical genomics at the University of Florida. An uncommon strength is her interdisciplinary track record—from gut microbiome links to Type 1 Diabetes to structural predictions of binding affinity—demonstrating both domain depth and practical translational impact.
12 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy Microbiology General, Doctor of Philosophy Microbiology General at University of Florida, FL
Pontifical Catholic University of Rio de Janeiro
Master's degree Computer Science, Master's degree Computer Science at Pontifícia Universidade Católica do Rio Grande do Sul
Doctor of Philosophy (PhD) Microbiology and Cell Science, Doctor of Philosophy (PhD) Microbiology and Cell Science at University of Florida