Giovanni Parmigiani is Chair of the Department of Biostatistics and Computational Biology at the Dana Farber Cancer Institute and Associate Director for Population Sciences at the Dana-Farber/Harvard Cancer Center. He received a B.S. in Economics and Social Sciences at Università L. Bocconi, and a M.S. and PhD in statistics from Carnegie Mellon University. His research interests include models and software for predicting who is at risk of carrying genetic variants that confer susceptibility to cancer, specifically with respect to breast, ovarian, colorectal, pancreatic, and skin cancer. His research covers statistical methods for the analysis of high-throughput genomic data, such as for the analysis of cancer genome sequencing projects, integration of genomic information across technologies, and cross-study validation of genomics results. He is also interested in statistical methods for complex medical decisions, comprehensive models for lifetime history of chronic disease outcomes, decision trees, and dynamic programming. This includes Bayesian modeling and computation, multilevel models, decision theoretic approaches to inference, sequential experimental design, and Markov chain Monte Carlo methods. Dr. Parmigiani's work has been published in Science, the Journal of the American Medical Association, Cancer Research, the Journal of the American Statistical Association, the Journal of Clinical Oncology and the American Journal of Human Genetics.