Simone Rubinacci is a Group Leader at FIMM and a Research Fellow at Brigham and Women's Hospital and Harvard Medical School. He earned his DPhil from the Department of Statistics at the University of Oxford.
Simone's research leverages large-scale genomic datasets to uncover genetic relationships within individuals and across populations. His work focuses on identifying shared chromosomal segments (haplotypes) and exploring how genetic variation shapes diversity and influences disease. A significant aspect of his research involves developing statistical methods to extract meaningful insights from noisy genomic data, such as low-coverage whole-genome sequencing and SNP arrays. Currently, his primary focus is on characterizing structural variation in human genomes and investigating its implications for health. This research spans applications ranging from understanding population structure to uncovering the genetic basis of diseases, bridging fundamental genetic insights with translational applications.
Théo has a background in biology and bioinformatics, with a strong interest in human genetics, evolution, and the molecular basis of complex traits. He uses computational methods to study inheritance patterns and trait regulation in large-scale biobank datasets. Outside the lab, he enjoys bouldering, hiking, and music.