Curriculum Vitae
I am a computational biologist working in cancer genomics and multi-omics. My background spans computational oncology, single-cell analysis, transcriptomics, statistical modelling, machine learning, and reproducible computational workflows.
Professional Experience
Bioinformatician — Functional Oncology
- Analysed scRNA-seq data to study tumour plasticity and state transitions in lung adenocarcinoma, including trajectory inference and RNA velocity.
- Integrated miRNA-seq, bulk RNA-seq, DNA methylation, immune deconvolution, and genomic alterations through multi-omics analysis with MOFA.
- Applied statistical and machine-learning models to immune activation, PD-L1/IFNG phenotypes, clinical variables, and biomarker questions.
Biotechnologist — Genotyping
High-throughput TaqMan RT-PCR genotyping for engineered mouse-model workflows.
Research & Thesis
MSc Thesis — Computational Oncology
- Integrated methylation and RNA-seq data to construct a reference atlas of neutrophil subtypes.
- Applied immune deconvolution across multi-cancer cohorts and investigated tumour-associated neutrophil signatures in relation to prognosis and genomic instability.
- Investigated immune-derived cfDNA signals as potential non-invasive biomarkers.
Paediatric ALL subtype classification
Machine-learning research on subtype classification from large-scale genomic data using XGBoost, neural networks, and SHAP-based interpretation.
Presentations & Scientific Meetings
Selected scientific presentations
Machine-learning research presented in the context of BITS 2024 and the 36th Pezcoller Symposium.
Education
MSc Quantitative and Computational Biology
BSc Biological Sciences
Technical Profile
Programming
R · Python · Bash
Analysis ecosystems
Seurat · Scanpy · tidyverse · DESeq2 · scikit-learn · PyTorch
Computational biology
scRNA-seq · bulk RNA-seq · miRNA-seq · multi-omics integration · statistical
modelling · machine learning · Nextflow · reproducible workflows
Languages
Italian — native
English — C1+