About

Hi, I’m Lorenzo. I’m a Master’s student in Computer Science at Sapienza University (Rome). I like building small, concrete things: ML experiments, pipelines, and prototypes where you can actually see what changes when you tweak a piece. The best moment is when a messy dataset starts to make sense and patterns show up that tell you something real.

I’m mostly interested in computation as a tool for analysis — bioinformatics, physics, information theory, and anywhere models + data can answer real questions. But yes, I also like the “computer stuff”: coding, making systems run, and the practical engineering details.

Based in Italy • Last updated: February 2026

Education

  • MSc Computer Science 2025–Present
    Sapienza University of Rome
  • BSc Applied Computer Science & AI 2022–2025
    Sapienza University of Rome · 110 cum laude
  • Diploma di Liceo Scientifico 2017–2022
    Liceo Scientifico A. Romita · 100 e lode

What I build

  • ML pipelines: training + evaluation + interpretation.
  • Vision experiments: detection/localization/segmentation pipelines.
  • Graph ML: biological networks, social interaction networks, and general network data analysis.
  • Data analysis: cleaning messy datasets, extracting and interpreting patterns
  • 3D / synthetic data: small Blender pipelines for labeled datasets.
  • Web & small apps: lightweight APIs and tools for site and apps

Projects and writeups live in Projects and Notes.

Tools & skills

ML & data

  • Core: Python, NumPy, pandas, Matplotlib
  • ML/DL: PyTorch, PyTorch Lightning, scikit-learn
  • Experiment workflow: notebooks, reproducible runs, clean evaluation

Vision & graphs

  • Vision: OpenCV, torchvision
  • Graphs: PyTorch Geometric, NetworkX, Gephi
  • Typical tasks: heatmaps/masks → post-processing → bounding boxes → classification

Bioinformatics / network medicine

  • Tools: SWIMmeR, SaveRunner,WGCNA, Enrichr
  • Work: enrichment analysis, disease module analysis, correlation analysis, network-based interpretation, interactome workflows
  • Supporting stack: pandas/NumPy for cleaning + reproducible notebooks for analysis

3D, web, and engineering

  • 3D / rendering: Blender (dataset generation, lighting, domain randomization)
  • Web: HTML/CSS, JavaScript, OpenAPI, REST APIs
  • Backend basics: SQL fundamentals, small services/tools
  • Workflow: Git, Docker (when needed)

I’m mostly Python-first: I prefer using the right libraries and writing clean glue code over “collecting” languages.