Francesca Chiaromonte Named Institute of Mathematical Statistics (IMS) Fellow. The award for outstanding contributions to methodology for the analysis of large, complex and structured data. The congratulations of Sabina Nuti, Rector of Sant'Anna School

Francesca Chiaromonte, Full  Professor of Statistics, Dorothy Foehr Huck and J. Lloyd Huck Chair in Statistics for the Life Sciences, The Pennsylvania State University & Sant'Anna School (Pisa Italy) has been named Fellow of the Institute of Mathematical Statistics (IMS). Francesca Chiaromonte received the award for outstanding contributions to methodology for the analysis of large, complex and structured data, in particular to the fields of sufficient dimension reduction and envelope model, for outstanding interdisciplinary work in the “Omics” and in the biomedical sciences, and for leadership in interdisciplinary training and mentoring efforts.

The designation of IMS Fellow has been a significant honor for over 85 years. Each Fellow is assessed by a committee of their peers and has demonstrated distinction in research or leadership that has profoundly influenced the field. Created in 1935, the Institute of Mathematical Statistics is a member organization that fosters the development and dissemination of the theory and applications of statistics and probability. The IMS has 4,200 active members throughout the world. Approximately 10% of the current IMS membership has earned the status of fellowship. 

Francesca Chiaromonte was immediately congratulated by Sabina Nuti, Rector of the Sant'Anna School, on behalf of the entire academic community. “This is a recognition by one of the most prestigious scientific institutions in the world in the mathematical and statistical disciplines, which confirms, once again, the fundamental contribution of Francesca Chiaromonte to the development of the activities of the Sant'Anna School, with particular reference to those of the Institute of Economics and the Department of Excellence EMbeDS (Economics and Management in the era of Data Science)”.