MSc Bioinformatics & Computational Genomics
University of Milan. Building depth in statistics, programming, genomics and computational methods.
About
An interdisciplinary route into computational biology.
My background crosses liberal arts and sciences, molecular-biology research, education and data science. The common thread is an interest in complex problems that demand both analytical structure and domain understanding.
I am now pursuing an MSc in Bioinformatics & Computational Genomics, developing the statistical, computational and genomic foundations to work more deeply with biological data.
Trajectory
Different disciplines, one analytical thread.
MRes Tissue Engineering for Regenerative Medicine
University of Manchester. Molecular-biology research and gene-therapy modelling around a genetic muscle-wasting disease.
BSc Liberal Arts & Sciences
Maastricht University. Interdisciplinary research, critical thinking and problem framing.
Science coordination & education
Experience designing national examinations and later experimenting with generative-AI tools in education.
Capabilities
Skills are grouped by how I use them.
Programming
Python · R · SQL · Bash · Rust
Statistics & ML
Regression · Classification · Clustering · PCA · Model evaluation
Data & engineering
Pandas · NumPy · Git · Unix · Docker · Reproducible pipelines
Scientific direction
Bioinformatics · Computational genomics · Graph modelling · Biological data analysis
Publication
Cell-mediated exon skipping normalizes dystrophin expression and muscle function in a new mouse model of Duchenne Muscular Dystrophy
This co-authored publication provides biological context for the graph cross-correction modelling project.
Read publication ↗