Mentoring
PhD Thesis Co-Advisor
2021 – 2024
Department of Mathematics Politecnico di Milano
Alessandra Ragni – Statistical Methods for Hierarchical and Recurrent Event Data in Learning and Healthcare Analytics (PhD in Data Analytics and Decision Sciences).
Master Thesis Advisor
2024
Politecnico di Milano – MSc Mathematical Engineering
Chiara Danesi – Time-varying Cox shared frailty models for the prediction of university students dropout.
Alessio Frezza – Algorithmic Improvements for Multilevel Logistic Cluster-Weighted Model Estimation: Development and Evaluation of New Variants.
Greta Camplese – Semi-parametric cluster-weighted multilevel models for two-levels clustering.
Francesca Pessina – Profiling Healthcare Providers in Lombardia via Semi-Parametric Multilevel Generalized and Time-to-Event Models.
Alessandra Sala – Multilevel Multivariate and Hurdle Models to predict academic short-term performance through online admission test.
2023
Politecnico di Milano – MSc Mathematical Engineering
Giulia Bergonzoli – Ordinal Mixed-Effects Random Forest: an innovative statistical method to perform learning analytics.
Luca Caldera – Multilevel logistic cluster-weighted model for profiling and clustering of heart failure patients in Lombardy region using administrative database.
Giulia Romani – Time-Varying Shared Frailty Cox Models for the Analysis of University Students Dropout.
Alessio Tranchida – Multinomial multilevel models for predicting Master students’ careers at Politecnico di Milano.
Davide Lo Piccolo – SpMEMs: an R package for semi-parametric mixed-effects models.
Daniel Ippolito – Blended teaching evaluation through Multilevel Propensity Score.
2022
Politecnico di Milano – MSc Mathematical Engineering
Mirko Giovio – Survival models for predicting student dropout at university across time.
2021
Politecnico di Milano – MSc Mathematical Engineering
Agostino Lurani – A neural network approach to survival analysis with time-dependent covariates for modelling time to Cardiovascular diseases in HIV patients.
Luca Pirazzini – Time-Invariant and Time-Dependent Cox Models for Predicting Student Dropout at University.
Master Thesis Co-Advisor
2025
Politecnico di Milano – MSc Mathematical Engineering
Ardiana Prekazi – Joint Modelling of Re-hospitalizations and Mortality Through Discrete Bivariate Frailty in Heart Failure Patients.
Gilda Matteucci – Integration of Radiomic Features and Intra-Patient Heterogeneity of Colorectal Cancer Metastases for Prognostic Modelling.
2024
Politecnico di Milano – MSc Mathematical Engineering
Sofia Moroni – Non-Parametric Survival Learning for Prognostic Modelling Integrating Radiomic Features.
2023
Politecnico di Milano – MSc Mathematical Engineering
Lorenzo Angiolini – Model-based clustering of lifetime data with frailties and random covariates for the profiling of COVID-19 heart failure patients.
2022
Politecnico di Milano – MSc Mathematical Engineering
Riccardo Scaramuzza – Joint modelling of hospitalizations and survival in Heart Failure patients: a discrete non-parametric frailty approach.
2020
Politecnico di Milano – MSc Mathematical Engineering
Veronica Marino – An Application of Neural Network for Learning Analytics.
Andrea Maggioni – Semi-parametric generalized linear mixed-effects model: an application to Engineering BSc dropout analysis.
2019 – 2016
Politecnico di Milano – MSc Mathematical Engineering
Massimo Pellagatti – Generalized Mixed-Effects Random Forest for classification: an application to predict university students’ dropout (2019).
Luca Fontana – Statistical analysis of engineering BSc dropout through mixed-effects models (2018).
Matteo Rivolta – Metodi di imputazione per dati mancanti: applicazione al dataset INVALSI (2016).
Internship Students Host
2024 – 2022
ENSTA Paris
Théo Cadene (2024) – Learning Analytics, Erasmus+ program.
Marceau Germe (2022) – Modelling student dropout at Politecnico di Milano in R, Erasmus+ program.