Theory and Methods: Bayesian variable selection, Graphical Models, Statistical Computing, Wavelets. Applications in Chemometrics, Large-scale Genomic data, Neuroimaging and Structural Bioinformatics
Dr. Vannucci is Noah Harding Professor of Statistics and Department Chair. She is also an adjunct faculty member of the UT M.D. Anderson Cancer Center, TX, and the Rice Director of the Interinstitutional Graduate Program in Biostatistics. Dr. Vannucci is generally interested in the development of statistical models for complex problems. Her methodological research has focused in particular on the theory and practice of Bayesian variable selection techniques and on the development of wavelet-based statistical models and their application. She also works in the areas of graphical models and nonparametric Bayes. Her research is often motivated by real problems that need to be addressed with suitable statistical methods. Methodologies developed by Dr. Vannucci have found applications in chemometrics and, more recently, in high-throughput genomics and in neuroimaging. Dr. Vannucci has also an interest in structural bioinformatics and, in particular, on the important problem of protein structure prediction. Dr. Vannucci was the recipient of an NSF CAREER award in 2001. She is an elected Member of the International Statistical Institute (ISI), and an elected Fellow of the American Statistical Association (ASA), the Institute of Mathematical Statistics (IMS), the American Association for the Advancement of Science (AAAS), and the International Society for Bayesian Analysis (ISBA). She holds a Laurea (B.S.) in Mathematics and a Ph.D. in Statistics, both from the University of Florence, Italy."