I'm a Health Researcher at IRCCS Sant'Orsola in Bologna, where I develop computational methods to predict antimicrobial resistance, discover patient phenotypes, and make sense of high-dimensional omics data. My work spans MALDI-TOF mass spectrometry, multi-omics integration, genomics, and metagenomics, always with a focus on interpretability and clinical impact. I work in the Computational Genomics Unit, part of the Multi-Omics and Health-Care Data Analytics Unit at Sant'Orsola Hospital, and collaborate closely with Prof. Gastone Castellani's Physics4MedicineLab.
PhD in Health and Technologies (University of Bologna, 2026), supervisor Prof. Gastone Castellani.
MaldiSuite - a Python ecosystem for MALDI-TOF spectral processing and analysis in antimicrobial resistance research. Visit the MaldiSuite website.
Three sklearn-compatible packages that chain into an end-to-end clinical AMR pipeline: preprocess with MaldiAMRKit, harmonise across batches/sites with MaldiBatchKit, classify with MaldiDeepKit.
pip install maldisuite # MaldiAMRKit + MaldiBatchKit + MaldiDeepKitPreprocess |
Harmonise |
Classify |
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| Package | Description | PyPI | Downloads |
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| combatlearn | Scikit-learn compatible ComBat batch-effect correction |  |
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| ResPredAI | AI model to predict resistances in Gram-negative bloodstream infections |  |
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| phenocluster | Unsupervised clinical phenotype discovery with survival and multistate modeling |  |
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| nestkit | Nested cross-validation with calibration, threshold optimization, and statistical tests |  |
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| Project | Description |
|---|---|
| CATS | Automated Cas9 nuclease comparison with ClinVar integration |
| CAMISIM-BrokenStick | Broken stick model extension for metagenomic simulation |
| APOBECSeeker | APOBEC-style mutation identification from multiple sequence alignment |
- AMR & clinical machine learning - MALDI-TOF, supervised & generative learning, cross-site harmonisation · MaldiSuite, ResPredAI
- Infectious risk & pathogen surveillance - patient phenotyping, survival & multi-state models, metagenomic surveillance · phenocluster, CAMISIM-BrokenStick
- Computational genomics - structural variants, somatic calling, long-read sequencing · APOBECSeeker, CATS
- Computational methodologies - open-source tools, reproducible pipelines · combatlearn, nestkit, MaldiBatchKit
The full picture is on the research page of my website.
Bonazzetti, C., Rocchi, E. et al. Artificial Intelligence model to predict resistances in Gram-negative bloodstream infections. npj Digital Medicine 8, 319 (2025). Code: ResPredAI.
A curated list with BibTeX lives on my website; for the complete record, see my Google Scholar profile.