Rosanna Gualdi

PhD Student

Department of Statistical Sciences "Paolo Fortunati"

Academic discipline: SECS-S/04 Demography

Curriculum vitae

Download Curriculum Vitae (.pdf 248KB )

EDUCATION

Currently PhD Student in "Future Earth, Climate Change and Societal Challenges".

Second Cycle Degree in Statistics, Economics and Business Level Department of Statistical Sciences “Paolo Fortunati” at Alma Mater Studiorum University of Bologna, Italy (2020). Thesis Title: Non-Parametric Statistical Study of Radioxenon Measurements for the
Verification of The Comprehensive Nuclear Test-Ban Treaty (CTBT). Supervisor: Michele Scagliarini, Giuseppe Ottaviano, Antonietta Rizzo and Franca Padoani).
First Cycle Degree in Bio-Demographic Statistical Sciences at Alma Mater Studiorum University of Bologna, Italy (2016). Thesis title “Longevity Areas in North-Eastern Italy: An Analysis by Socio-Health Districts”
(Supervisor: Alessandra Samoggia and Aldopaolo Palareti).

ARTICLES

Scagliarini, M., Gualdi, R., Ottaviano, G., & Rizzo, A. (2023). "Detection of anomalous radioxenon concentrations: A distribution-free approach." Environmetrics, e2804. https://doi.org/10.1002/env.2804

POSTERS

G. Ottaviano, M. Scagliarini, R. Gualdi, A. Rizzo, F. Padoani. “Non-parametric study of the radioxenon data distribution, measured at the noble gas stations of the Internal Monitoring System of the CTBTO”. SnT 2021 (CTBT: Science and Technology Conference).

CONGRESSES

M. Scagliarini, R. Gualdi, G. Ottaviano, A. Rizzo. “Comparing Nonparametric Change-Point Control Charts for Detecting Radioxenon Anomalous Concentrations”. ENBIS 2022 Trondheim Conference (European Network for Business and Industrial Statistics).

G. Ottaviano, M. Scagliarini, A. Rizzo, R. Gualdi, S. Guernelli, C. Sanguigni, L. Ferri, F. Padoani. “Statistical study of the IMS 133Xe data distributions using both a parametric and a non-parametric method”. SnT 2021 (CTBT: Science and Technology Conference).

M. Scagliarini, R. Gualdi, G. Ottaviano, A. Rizzo, F. Padoani. “A Distribution-Free Approach for Detecting Radioxenon Anomalous Concentrations”. SIS 2021 (50^th edition of the Scientific Meeting of the Italian Statistical Society).

Download Complete CV attached.