Daniela Calvetti is Professor and Chair of Mathematics in the College of Arts and Sciences. In her current research she combines mathematical modeling, numerical analysis and Bayesian inference to design predictive models. Her most recent publications, almost all coauthored with her graduate students, have focused on computational predictive models of brain cellular metabolism, in-vitro competition of different strains of HIV-1, a mathematical framework to improve the specificity of breast cancer detection and a more effective way to detect focal sources in the MagnetoEncephaloGraphy inverse problem. Her new ongoing projects include computational methods for particle filters, mathematical frameworks for the design of piezoelectric elements with specific properties and for understanding how the psychology of the markets affect option prices.
Dr. Calvetti has published over 100 refereed articles and is the coauthor of the monographs Bayesian Scientific Computing and Computational Mathematical Modeling: an integrated approach across scales. She completed her undergraduate work in Mathematics at the University of Bologna, Italy, and received her doctorate in Mathematics from the University of North Carolina at Chapel Hill.