Data Science student at Milano-Bicocca. Turning raw data into meaningful insights through machine learning, statistical modelling, and business intelligence.
Regularized LDA + KNN on MNIST across 5 noise types. Ridge regularization analysis with τ parameter tuning.
Bachelor's thesis investigating noise-regularization interaction in Regularized LDA + KNN for MNIST digit recognition. 91.75% baseline accuracy tested across 5 noise types (Gaussian, Salt & Pepper, Blur, Zigzag, Speckle).
OLS regression and correspondence analysis on 379 mobile models across 16 brands. R²=0.816. Identified RAM as the strongest price predictor at +$59.77 per GB increase.
R implementation of DISCO — a Density-based Internal Score for evaluating Clustering Outcomes. Provides a robust alternative to traditional cluster validation indices.
Full relational DBMS design for a university academy — ER modelling, relational schema, and SQL queries covering student, staff, device, and financial management.
I'm a Data Science student at the University of Milano-Bicocca with a background in Data Analytics from the Università degli Studi della Campania "Luigi Vanvitelli".
My work sits at the intersection of statistical modelling, machine learning, and business intelligence. I enjoy building interpretable, white-box models and communicating data stories clearly — whether through code, dashboards, or visual analysis.
I'm actively looking for internship or graduate opportunities in data science or analytics roles.
B.Sc. Data Analytics — Università della Campania Luigi Vanvitelli
M.Sc. Data Science — Università degli Studi di Milano-Bicocca (ongoing)
Milan, Italy — open to remote and relocation
iOS development experience with Swift and Xcode — built production-quality apps including nikeLikeApp and Flourish.
Data Science · Machine Learning · Business Intelligence · Data Analytics
I'm currently looking for internship and graduate opportunities. If you have a role, project, or just want to connect — I'd love to hear from you.