Andrea's research interests lie at the intersection between epidemiology, genetics and statistics. Andrea has authored and co-authored both methodological and applied papers focused on leveraging large-scale epidemiological datasets to identify novel socio-demographic, metabolic, and genetic markers of common complex diseases. He has extensive expertise in statistical genetics and has been working with large-scale exome and genome sequencing data. He is co-leading two major international consortia: the COVID-19 host genetic initiative and the INTERVENE consortium. He has initiated the FinRegistry project. FinRegistry uses nationwide registry data to build machine learning models that will help to better understand and predict the onset of diseases in the population of Finland. His research vision is to integrate genetic data and information from electronic health records/national health registries to enhance the early detection of common diseases and public health interventions.