Curriculum Vitae

MSc Stochastics and Data Science

University of Turin, Italy — Grade: 109/110

Thesis: Efficient estimation of time-to-event models and quantile treatment effects under right-censoring. Developed and validated asymptotic properties of an extension of a causal inference method for right-censored data, providing a robust framework for estimating treatment effects in survival settings.

Supervisors: Matteo Giordano, Stijn Vansteelandt.

Coursework: Probability Theory, Statistical Inference, Stochastic Processes, Multivariate Statistical Analysis, Functional Analysis.

Exchange Semester (Erasmus+)

Ghent University, Belgium

Coursework: Causal Machine Learning, Deep Learning, Natural Language Processing.

BSc Mathematics for Finance and Insurance

University of Turin, Italy — Grade: 106/110

Thesis: One-dimensional and two-dimensional random walk with extension to Skew walk and non-Markovian walks.

Supervisor: Cristina Zucca.

Coursework: Probability and Statistics, Numerical Analysis, Mathematics for Finance and Insurance, Linear Algebra, Analytical Methods.

Data Scientist

Italdesign Giugiaro, Turin, Italy

Developed forecasting models using ARIMA/SARIMA, XGBoost and LSTM for revenue time-series prediction. Developed unsupervised learning projects using HDBSCAN and dimensionality-reduction techniques to identify structure in complex project data. Implemented complex SQL queries for large-scale data extraction and integration.

Research Intern

Department of Computer Science, University of Turin — in collaboration with the Italian Ministry of Foreign Affairs and Intesa San Paolo

Developed a machine learning model to predict geopolitical risks, incorporating an interactive visualization for analysis. Applied Explainable AI (XAI) techniques, specifically gradient-based methods, to enhance the interpretability of neural network models.

Integrating XAI for Predictive Conflict Analytics

Macis L., Tagliapietra M., Castelnovo A., Regoli D., Greco G., Cosentini A., Pisano P., Carroccetto E.

Proceedings of the xAI 2024 Late-Breaking Work and Demos, Valletta, Malta.

Probabilistic modelling, stochastic processes, state-space models, dynamical systems, time-series modelling, survival modelling, statistical inference.

Supervised and unsupervised learning, deep learning, explainable AI.

Python (NumPy, Keras, pandas, scikit-learn, matplotlib), MATLAB, R, C++, SQL, Git.

Treasurer and volunteer

AVIS — Italian National Blood Donor Association