Dr. Sebastiani is a multidisciplinary biostatistician, with a long track record of developing new methodologies in Bayesian statistics, decision theory, machine learning, artificial intelligence, and statistical experimental design, in addition to teaching, mentoring, and leading interdisciplinary research projects.

She introduced innovative Bayesian techniques for the analysis of genomic and genetic data and was a pioneer in using networks to model the genetic and phenotypic basis of the complications of sickle cell anemia. She is also a renowned biostatistician in the fields of the biology and epidemiology of human aging and longevity: she introduced original methods to design observational studies of human longevity, and to discover genetic and non-genetic risk factors that contribute to healthy aging. She is Co-PI of the NIH funded Longevity Consortium, and of the Long Life Family Study.

She is also multiple PI of a project to characterize the molecular targets of the protective APOE2 allele, and of a project that will generate multi-omics profiles of humans and other species to discover targets for healthy aging (Integrative longevity Omics). Her current research focuses on the genetics and epidemiology of extreme human longevity, analysis of rare genetic variants, and integrative analysis of multi-omics data using statistical and machine learning methods.