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  • Center for Mind / Brain Sciences - The University of Trento
  • Trento, Italy
  • 21:46 (UTC +01:00)
  • LinkedIn in/vittorioiacovella

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viacovella/README.md

Hi there, I'm Vittorio 👋

Turning complex scientific data into robust software solutions.

I am a physicist and neuroscientist. I currently work on Research Data Management and Research Software Development. I try everyday to bridge the gap between experimental research and software solutions.

Currently, I specialize in Python, FastAPI, and Data Standards (BIDS, DICOM), building pipelines that move data from experimental research to actionable insights.


Tech Stack

  • Backend & API: Python (FastAPI, Flask), AsyncIO, Pydantic
  • Data & Science: Pandas, NumPy, DICOM/Pydicom, BIDS Standard
  • Infrastructure: Docker, Git, Linux
  • AI & ML: Google Gemini API, PyTorch (Basics)
  • Quality & Modern Tools: Ruff (Linting/Formatting), GitHub Actions (CI/CD basics)

Featured Projects

Tech: FastAPI Orthanc Pydantic Docker A robust microservice connecting hospital RIS systems with MRI scanners. It automates patient data entry, reducing human error and streamlining the imaging workflow.

  • Key Focus: Async communication, Medical Standards (DICOM), Error Handling.

Tech: Pydantic JSON Schema CI/CD A strict validation library for complex experimental datasets. It enforces data integrity and schema compliance to ensure scientific reproducibility.

  • Key Focus: Data Modeling, Type Safety, Schema Design.

Tech: Google Gemini API Flask Plotly An experimental web app that turns natural language questions into interactive data visualizations.

  • Key Focus: LLM Integration, Prompt Engineering, Dynamic Plotting.

Tech: FastHTML HTMX Plotly A modern, lightweight dashboard for browsing large scientific catalogs with server-side rendering speeds.

  • Key Focus: Modern Web Dev, Prototyping, Performance.

Continuous Learning & Insights

I actively track the evolution of AI in Science and Research Data Management.

  • Check out my Curated Research Notes: A structured collection of papers and resources on Foundation Models, Self-Supervised Learning, and FAIR data practices.
  • I shared these insights during a dedicated LinkedIn campaign: "DRAI January" in Jan 2026.

What I'm working on

  • Developing an extension for the BIDS standard (Brain Imaging Data Structure).
  • Exploring Foundation Models for scientific discovery.
  • Refining my DevOps skills (Kubernetes, Advanced CI/CD).

LinkedIn

Pinned Loading

  1. nibs-bids-sandbox nibs-bids-sandbox Public

    draft repository for representing a NIBS experiment with BIDS

  2. ard-validator ard-validator Public

    An attempt to build an animal cognition research data schema and validator

    Python

  3. dicom-worklist-validator dicom-worklist-validator Public

    A set of containers to receive, validate and transform patient / study data into DICOM modality worklist information

    Python

  4. google-ai-sandbox google-ai-sandbox Public

    A sandbox to test AI agent capabilities

    HTML

  5. bids-data-catalog bids-data-catalog Public

    A web application to browse BIDS data

    Python