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Abstract: TBD

Bio: Florentina is a faculty member of the Department of Statistics and Data Science, a member of the Center for Applied Mathematics (CAM) and a member of the Machine Learning Group in CIS.  As a member of the CIS Diversity and Inclusion Council, she is committed to promoting the diversity of the work force in data-science disciplines.

Her research is broadly centered on statistical machine learning theory and high-dimensional statistical inference. Florentina is interested in developing new methodology accompanied by sharp theory for solving  a variety of problems in data science. Recent research projects include high-dimensional latent-space clustering, cluster-based inference, network modeling, inference in high dimensional models with hidden latent structure and topic models. Florentina continues to be interested in the general areas of model selection, sparsity and dimension reduction in high dimensions, and in applications to genetics, systems immunology, neuroscience, sociology, among other disciplines.

Her research is funded in part by the National Science Foundation (NSF-DMS). She is a Fellow of the Institute of Mathematical Statistics (IMS). Florentina has served or am currently serving as an  Associate Editor for  a number of  journals (the Annals of Statistics, Bernoulli, JASA, JRSS-B, EJS, the Annals of Applied Statistics).