Leonardo Egidi - Statistician

Students

I have supervised 19 MSc students and 2 Bachelor students in Statistics and Data Science on different topics. I supervise and co-supervise also 3 PhD students.

PhD Supervision

  • Roberto Macrì Demartino: PhD in Statistical Sciences, University of Padova, “XXXVII Cycle” (2021-2024). Co-supervisor: Nicola Torelli.
  • Giovanni Santacatterina: PhD in Artificial Intelligence and Applied Data Science (ADSAI), University of Trieste, “XXXVIII Cycle” (2022-2025). Co-supervisor: Giulio Caravagna.
  • Badar ud din Taher: PhD in Artificial Intelligence and Applied Data Science (ADSAI), University of Trieste, “XXXIX Cycle” (2023-2026). Co-supervisor: Nicola Torelli.

Thesis Supervision (MSc and Bachelor)

  • Mitja Briscik: Statistical models for predicting football match results: an application to the UEFA Champions League (Bachelor in Statistica e informatica per l’azienda, la finanza e l’assicurazione, University of Trieste, A.Y. 2018-2019).
  • Giuseppe Sassano: Statistical models for football match prediction: shots on target as a key factor (MSc in Scienze statistiche, University of Padova, A.Y. 2018-2019).
  • Anna Scussolin: An application of hierarchical models to assess insurability in credit lines (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2018-2019).
  • Francesco Guglielmo: Statistical models for SARS-CoV-2 epidemic data analysis in Italy (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2019-2020).
  • Federico Spatola: Statistical models for analyzing the SARS-CoV-2 epidemic in Italy (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2019-2020).
  • Cesare Farina Busetto: Development and comparison of statistical models for football match prediction (MSc in Scienze statistiche, University of Padova, A.Y. 2019-2020).
  • Niccolò Rossi: Expected Goals in Football: Statistical Learning Models for Match Results Prediction (MSc in Data Science and Scientific Computing, University of Trieste, A.Y. 2019-2020).
  • Laura Balasso: A Bayesian Approach to Estimate Covid-19 Reproduction Number in Italian Regions (MSc in Data Science and Scientific Computing , University of Trieste, A.Y. 2019-2020).
  • Lorenzo Fresco: A statistical learning approach for cross-contextual time-series forecasting (MSc in Data Science and Scientific Computing, University of Trieste, A.Y. 2019-2020).
  • Vincenzo Digiaro: Statistical models for predicting surrenders in life insurance products (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2019-2020).
  • Giacomo Coslevaz: Statistical and Machine Learning models for football match prediction (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2020-2021).
  • Andrea Scapini: Neural networks for football match result prediction (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2021-2022).
  • Alexa Pasquale: Bayesian methods for incorporating historical information in clinical studies (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2021-2022).
  • Mattia Sclabas: Comparing classical and Bayesian statistical models for electoral vote prediction in Italy (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2021-2022).
  • Giancluca Iacubino: Football match prediction models: a result-based approach using machine learning techniques (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2021-2022).
  • Giulio Fantuzzi: Statistical models for football match prediction: Dixon-Coles model implementation in R and application to Serie A 2021-2022 (Bachelor in Statistica e informatica per l’azienda, la finanza e l’assicurazione, University of Trieste, A.Y. 2022-2023).
  • Marco Pasetti: Telematics in insurance: traditional techniques and machine learning for car insurance pricing (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2022-2023).
  • Lorenzo Turrini: Statistical approaches to climate change: literature review and preliminary models (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2022-2023).
  • Marco Davide Ceruti: Analysis of football data: a comparison between classical and tie-inflated statistical models (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2022-2023).
  • Mauro Mariotto: Modelli previsionali per churn analysis (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2022-2023).
  • Aurora Michelin: L’emissione di anidride carbonica in ambito aziendale e il conseguente impatto sul riscaldamento globale: modelli statistici e studio della letteratura. (MSc in Scienze statistiche e attuariali, University of Trieste, A.Y. 2023-2024)
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