gabrielecorbo/bayesian-mixture-model-for-environmental-application

This project was realized for the Bayesian Statistics course, held at Politecnico di Milano, A.Y. 2022/2023.

Hi there 👋

I am a Mathematical Engineering - Statistical Learning student at Politecnico di Milano.

As you will see my projects are principally focused on the resolution of variuos problems through the implementation of Machine Learning models.

🏫 Education:

• MSc in Statistical Learning track of Mathematical Engineering at Politecnico di Milano
• Erasmus semester at TU Delft
• Alta Scuola Politecnica (Politecnico di Milano Honor Program)
• BSc in Mathematical Engineering at Politecnico di Milano

✉️ Get in Contact with me:

🚀 Skills:

🔨 Projects:

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• OASIS Project: The OASIS project, conducted by students of the Alta Scuola Politecnica in collaboration with Atlante, aims to provide a systematic and efficient approach to the deployment of electric vehicles charging stations.
• Nonparametric analysis of US dairy production and consumption: This project presents a nonparametric analysis of the evolution of dairy production and consumption in the United States from 1980 to 2021.
• Bayesian Mixture Model For Environmetal Application: Bayesian clustering of PM10 concentartion time-series, using Dirichlet process mixture models.
• Mixed and functional analysis models for studying Heart Failure (re)-hospitalizations: The main aim of this study is to provide statistically relevant methods for identifying the potentially high-risk patients in advance and understanding which are the main patient-level features that have an impact on the re-hospitalization.
• Machine Learning model that uses Photovoltaic system power output to detect malfunctions : Exploited machine learning techniques to create a classification model to detect PV anomalies.
• Estimating Client's Needs using Machine Learning : Exploited machine learning techniques to create a cross-platform web-app to recommend products based on clients' needs.
• Statistical analysis on biomechanical parameters : Linear regression and ANOVA on a dataset containing angles of various parts of the hip bone, in order to predict the lumbar lordosis angle and understand if a correlation holds between that parameter and the main pathology of a patient.

😄 Something about me:

• Florence,Italy ⚜️
• Check out my Letterbox profile to see my favourites films 📽️
• Basketball 🏀 and Football ⚽ fan