Fatonamurra N i

Applied statistical analysis and machine learning to microbiome abundance data to model cardiovascular disease risk. Preprocessed high-dimensional datasets, performed feature selection and dimensionality reduction, and built predictive models including Random Forest, SVM (CLR + RBF), Elastic Net, and XGBoost. Used SHAP for model interpretability to identify key microbial features in R. Supported hands-on training for biological data analysis and assisted participants with statistical analysis and reproducible workflows.

Applied statistical analysis and machine learning to gut microbiome abundance data to model cardiovascular disease risk. Preprocessed a high-dimensional dataset, performed feature selection and dimensionality reduction, and built predictive models including Random Forest, SVM (CLr + RBF), Elastic Net, and XGBoost. Used SHAP for model interpretability to identify key microbial features. Supported reproducible R workflows and hands-on training for biological data analysis, assisting participants with statistical analysis tasks during training sessions.

Internship experience focused on data science and machine learning for microbiome analytics, including data preprocessing, exploratory analysis, and model building with a focus on interpretability and reproducible analysis workflows.