Are you looking for inspiration for your Bachelor of Science thesis?
Here you can find a collection of theses written by Bocconi students on topics related to Machine Learning and more.

Share your thesis with us!

We would love to explore what you have done and many other students would find it extremely helpful.
Just send a single pdf file to bsmachinelearning@gmail.com indicating your name, your advisor's name, the title of your thesis, the course and the graduation year : )

BEMACS '25

Integrating Single-Cell RNAseq and Graph Neural Networks to Predict TP53 Mutation Status

Tommaso Ravasio

Prof. Francesca Buffa

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BEMACS '24

Inference with Complex Distributions: LDA and HDP in the Context of Topic Modeling

Giulio Pirotta

Prof. Antonio Lijoi

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BESS '24

Can Machine Learning Aid Econometrics? A Methodological Study on Heterogeneous Treatment Effects Estimation

Matilde Dolfato

Prof. Jerome Adda

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BEMACS '24

Enhancing Collaborative Filtering with Mixture Models: Theory and Applications

Tancredi Dorsi

Prof. Antonio Lijoi

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BEMACS '24

Predictive Modeling for Sales and Consumption in the Fast-Moving Consumer Goods Market: a Regression Analysis Perspective

Rebecca Benedetti

Prof. Jessica Jumee Kim

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BAI '24

An Overview on Multiview Learning and View Selection Methods

Beatrice Citterio

Prof. Bostond Tibor Szabo

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BAI '24

Stochastic Block Models for Community Detection in Graphs

Luca Gandolfi

Prof. Giacomo Zanella

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BEMACS '24

Graph Neural Networks: From Foundations to Temporal Applications

Marco Lomele

Prof. Luca Saglietti

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BEMACS '24

Statistical Models for Survival Data: Theory and Applications

Alessandro Morosini

Prof. Antonio Lijoi

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BEMACS '24

Bayesian Optimization for Database Management

Giulio Caputi

Prof. Omiros Papaspiliopoulos

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BEMACS '24

Exploring Transcriptional Interactions and Language Models for Single Cell RNA-seq Masked Value Prediction

Giacomo Cirò

Prof. Francesca Buffa

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BEMACS '24

An Approach to the Explanation of Annotator-level Differences in Toxicity Detection Through Irony

Luca Colaci

Prof. Kai Zhu

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BEMACS '24

Generative Modeling in AI and Stochastic Processes

Francesco Vacca

Prof. Omiros Papaspiliopoulos

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BEMACS '24

Advanced Statistical Methods in Network Analysis: the Role of Stochastic Block Modeling

Tommaso Vezzoli

Prof. Antonio Lijoi

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BEMACS '23

On the Granularity of Data: a Comparison Between Classical and Deep Learning Approaches for Time Series Forecasting

Giulia Paggini

Prof. Daniele Tonini

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