Summary
Anna Cuomo is an Associate Principal Scientist with nine years of experience developing integrative statistical models that connect genetic variation to single-cell expression, most recently leading analyses at AstraZeneca after a postdoctoral tenure at the Garvan Institute. She holds a PhD in Statistical Genetics from the University of Cambridge and has contributed to major consortia efforts including HipSci, the Human Cell Atlas, sc-eQTL Gen and the TenK10K project, where she analyzes WGS-derived common, rare and structural variants across immune cells from over 2,000 individuals. Skilled in large-scale single-cell RNA-seq, eQTL and GWAS analysis, she combines deep computational proficiency in Python and R with rigorous statistical modeling to uncover genotype–phenotype mechanisms. Notably, her background spans both computational method development and hands-on population-scale data leadership, bridging academic research and industry translation.
9 years of coding experience
6 years of employment as a software developer
High School, 100/100, High School, 100/100 at Vittorio Veneto
Doctor of Philosophy (Ph.D.), Biomathematics, Bioinformatics, and Computational Biology, Doctor of Philosophy (Ph.D.), Biomathematics, Bioinformatics, and Computational Biology at University of Cambridge
Bachelor's Degree, Ingegneria Matematica, 100/110, Bachelor's Degree, Ingegneria Matematica, 100/110 at Politecnico di Milano
TU Delft
Italian, English, French, Spanish, German