Valentina Di Francesco, M.S.
National Human Genome Research Institute
Office of Genomic Data Science
Laurea, Mathematics, University of Milan, Italy
M.S., Statistics, George Washington University, Washington, D.C.
Valentina Di Francesco is NHGRI's first Chief Data science Strategist and Director of the new Office of Genomic Data Science. In this role, she will provide leadership, strategic guidance and coordination for NHGRI activities, programs and policies in genomic data science.
Ms. Di Francesco joined NHGRI in 2014 and was the lead program director of the Computational Genomics and Data Science Program. She coordinated a diverse portfolio of genomic data science and computational biology grants and funding opportunities, and oversaw a grant portfolio that included model organism databases, and the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-Space (AnVIL) program. Ms. Di Francesco also contributed to several trans-NIH data science committees and activities, including the NIH Cloud Platforms Interoperability (NCPI) efforts.
Before joining NHGRI, Ms. Di Francesco was a program officer at the National Institute for Allergy and Infectious Diseases (NIAID) for more than 10 years. She was primarily responsible for the bioinformatics, structural genomics and systems biology programs at NIAID, where she initiated and established initiatives focused on the use of high-throughput "omics" technologies, the development of big-data management and integration tools, and predictive modeling of the host/pathogen molecular interaction networks.
Prior to NIAID, Ms. Di Francesco was at The Institute for Genomics Research (now the J. Craig Venter Institute) and at Celera Genomics, where she contributed to the development of tools for the computational structural and functional annotation of microbial and mammalian genomes, including the human genome. Prior to that, she was a visiting research fellow at the NIH Center for Information Technology where she was involved in developing statistical methods for protein structure prediction.
Last updated: March 25, 2022