SciTransfer
Organization

ISTITUTO NAZIONALE DI FISICA NUCLEARE

Italy's national nuclear and particle physics laboratory, building detectors, computing infrastructure, and applying physics techniques from neutrino experiments to cultural heritage.

Research institutemultidisciplinaryIT
H2020 projects
135
As coordinator
24
Total EC funding
€59.0M
Unique partners
1222
What they do

Their core work

INFN is Italy's primary research institution for nuclear and particle physics, operating national laboratories and participating in major international experiments at facilities like CERN. They design and build advanced particle detectors, accelerator components, and computing infrastructure that underpin some of the world's largest physics experiments. Beyond fundamental research, INFN applies its detector and simulation expertise to medical physics (proton therapy, medical imaging), cultural heritage diagnostics, and high-performance computing platforms. They are a major contributor to European research infrastructure, providing both hardware engineering and distributed data services to the scientific community.

Core expertise

What they specialise in

Particle physics detectors and accelerator technologyprimary
45 projects

Core expertise demonstrated across projects like AIDA-2020 (detector R&D), UFSD (ultra-fast silicon detectors), BESIIICGEM (gas electron multiplier trackers), EuroCirCol (collider design), and EuPRAXIA (plasma accelerators).

Neutrino and dark matter experimentsprimary
12 projects

Strong presence in neutrino oscillation and dark matter search projects including JENNIFER (Japan-Europe neutrino research), NITEC (directional dark matter detection), and multiple flavour physics collaborations.

Research computing and data infrastructureprimary
15 projects

Major role in distributed computing through INDIGO-DataCloud (as coordinator), EGI-Engage, HNSciCloud, and EOSC-related projects for European Open Science Cloud development.

5 projects

Contributed high-performance computing and simulation expertise to the Human Brain Project (HBP SGA1), covering neuromorphic computing, neurorobotics, and brain reconstruction.

15 projects

Coordinates and participates in numerous European Researchers' Night events (SHARPER) and outreach projects focused on young people, schools, and gender balance in physics.

Cultural heritage diagnosticsemerging
3 projects

Recent keyword cluster around cultural heritage indicates growing application of physics-based diagnostic techniques (imaging, spectroscopy) to art and archaeological conservation.

Evolution & trajectory

How they've shifted over time

Early focus
Brain simulation and detector R&D
Recent focus
Research infrastructure and technology transfer

In the early H2020 period (2014–2018), INFN focused heavily on brain simulation and neuroinformatics through the Human Brain Project, alongside foundational detector R&D and co-design approaches for high-performance computing. By 2019–2022, the focus shifted decisively toward research infrastructure sustainability, EOSC integration, neutrino oscillation experiments, dark matter searches, and technology transfer — including unexpected applications like cultural heritage. This evolution shows INFN moving from pure experimental physics toward making its infrastructure and techniques accessible to broader scientific and societal domains.

INFN is increasingly positioning itself as an infrastructure and technology transfer hub, applying particle physics expertise to domains like cultural heritage and open science platforms — making it a strong partner for cross-disciplinary infrastructure proposals.

Collaboration profile

How they like to work

Role: active_partnerReach: Global66 countries collaborated

INFN operates primarily as an active partner (99 participations vs. 24 coordinations), joining large international consortia rather than leading them — consistent with its role as a national lab contributing specialized capabilities to big-science collaborations. With 1,222 unique consortium partners across 66 countries, they are a genuine network hub with exceptionally broad connectivity. When they do coordinate, it tends to be in focused detector or computing infrastructure projects where their technical leadership is clear, making them a reliable and well-connected partner who brings both deep expertise and extensive networks.

INFN has collaborated with 1,222 unique partners across 66 countries, making it one of the most connected research organizations in H2020. Their network spans well beyond Europe, with strong ties to Japan (JENNIFER) and the US (MUSE), reflecting the global nature of particle physics collaborations.

Why partner with them

What sets them apart

INFN is one of Europe's few national-scale physics laboratories with end-to-end capability — from theoretical physics through detector engineering to petabyte-scale data infrastructure. Unlike university physics departments, they operate their own accelerator facilities and maintain permanent engineering teams capable of building production-grade detector systems. Their 135-project H2020 portfolio and 1,222-partner network make them an anchor institution: partnering with INFN connects you to a vast ecosystem spanning fundamental science, medical applications, computing infrastructure, and increasingly, cultural heritage and open science.

Notable projects

Highlights from their portfolio

  • INDIGO-DataCloud
    INFN-coordinated project with EUR 2.1M funding to build distributed data infrastructure for global scientific exploitation — showcases their computing infrastructure leadership.
  • UFSD
    Coordinated EUR 1.7M ERC-funded project on ultra-fast silicon detectors, demonstrating INFN's frontier capability in detector technology that enables discoveries across physics.
  • EUROfusion
    Long-running fusion energy roadmap implementation (2014–2022), reflecting INFN's involvement in Europe's largest energy research initiative as a third-party contributor.
Cross-sector capabilities
healthdigitalspacesecurity
Analysis note: Profile based on 30 of 135 projects shown in detail plus aggregate statistics. With 135 H2020 projects and EUR 59M in funding, data richness is excellent. The keyword evolution analysis is robust given the large sample size.