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about us research technology projects education collaborations news scopus intranet


Cybersecurity Made In Europe LABEL

To help European cybersecurity companies position themselves on the market and be recognized as European, the European Cyber Security Organisation (ECSO) has initiated the Cybersecurity Made in Europe Label. This initiative involves introducing an industry-driven quality label, designed to promote European cybersecurity companies and increase their visibility on the European and on the global market. The Label will contribute strongly toward a stronger vision of a cyber-secure digital Europe.

DUCA: Data Usage Control for empowering digital sovereignty for All citizens

1 Gennaio 2023 – 31 Dicembre 2026

The Internet of Everything has led to a surge in connected devices, resulting in the generation of a huge amount of data. With the support of the Marie Skłodowska Curie Actions programme, the DUCA project aims to provide a comprehensive framework to address the growing concerns around data privacy and protection. Its goal is to empower European citizens and organisations to take control of their data, ensuring confidentiality and personal data protection. DUCA’s framework comprises a set of security and privacy-enhancing solutions, which will be platform-independent to enable compatibility with various architectures and deployment models. The project has identified three use cases: smart energy, usage control for Big Data and artificial intelligence, and collaborative mobility.

SYNAPSE: An Integrated Cyber Security Risk & Resilience Management Platform, With Holistic Situational Awareness, Incident Response & Preparedness Capabilities

1 Gennaio 2023 – 31 Dicembre 2026

SYNAPSE aims to design, develop & deliver an Integrated Cyber Security Risk & Resilience Management Platform, with holistic Situational Awareness, Incident Response & Preparedness capabilities.

EMERALD: Evidence Management for Continuous Certification as a Service in the Cloud

1 Novembre 2023 – 30 Ottobre 2026

Cloud-based services have grown from basic computing services to complex ecosystems, comprising (virtual) infrastructure, business processes and application code. These advanced services also increasingly leverage the usage of Artificial Intelligence, including Machine Learning or Natural Language Processing techniques, raising the complexity even higher. Due to the cascade of dependencies among the different products and services, the need arose to bring more agility to the certification process of cloud-based services, e.g., using continuous monitoring and assessment, as evidenced by references to it in the certifications of the EU Cybersecurity Act (EU CSA). To transform the continuous assessment and certification concept into the complete realization of a Certification-as-a-Service (CaaS), several challenges need to be solved. The design and implementation of the EMERALD CaaS solution leverages the H2020 project MEDINA’s outcomes and advances them to TRL 7 in the EMERALD core. Two PoCs will be provided, one for composite certification and one for mapping requirements to upcoming AI certification schemes. EMERALD will pave the road towards CaaS for continuous certification of harmonized cybersecurity schemes.

HPC-QS – High Performance Computer and Quantum Simulator hybrid
December 1, 2021 – November 30, 2025

The aim of HPCQS is to prepare European research, industry and society for the use and federated operation of quantum computers and simulators to overcome the most difficult computational challenges.

6Green – Ensuring energy-efficient 5G and 6G networks

01/01/2023 – 31/12/2025

The 6Green project aims to conceive, design, and realise an innovative service-based and holistic ecosystem, able to extend “the communication infrastructure into a sustainable, interconnected, greener end-to-end intercompute system” and promote energy efficiency across the whole 5/6G value-chain. The ultimate objective is to enable and to foster 5/6G networks and vertical applications reducing their carbon footprint by a factor of 10 or more.


01/01/2023 – 31/12/2025

The EDGELESS project aims to leverage the serverless concept across all levels of the edge-cloud continuum to fully benefit from diversified and decentralized computational resources available on-demand close to where data is produced or consumed. In particular, we aim to realize efficient and transparent horizontal pooling of resources on edge nodes with limited capabilities or specialized hardware, seamlessly integrated with cloud resources, which represents a huge step forward compared to today’s vertical offloading solutions.


01/10/2020 – 31/08/2024

The EU-funded HumanE-AI-Net project brings together leading European research centres, universities and industrial enterprises into a network of centres of excellence. Leading global artificial intelligence (AI) laboratories will collaborate with key players in areas, such as human-computer interaction, cognitive, social and complexity sciences. The project is looking forward to drive researchers out of their narrowly focused field and connect them with people exploring AI on a much wider scale. The challenge is to develop robust, trustworthy AI systems that can ‘understand’ humans, adapt to complex real-world environments and interact appropriately in complex social settings. HumanE-AI-Net will lay the foundations for designing the principles for a new science that will make AI based on European values and closer to Europeans.

1 gennaio 2020 – 31 dicembre 2024

SoBigData ++ è il progetto europeo che si configura come l’implementazione del precedente Progetto SoBigData (2015-2019). Il progetto ha l’obiettivo di dare vita ad un’infrastruttura di ricerca distribuita, paneuropea e multidisciplinare per l’analisi dei big social data, e al contempo supportare il consolidamento di una comunità di ricerca europea interdisciplinare, finalizzata all’utilizzo del social mining e dei big data per comprendere la complessità del nostro contemporaneo, ormai una società interconnessa a livello globale.

Scientific Large-scale Infrastructure for Computing/Communication Experimental Studies – Starting Community

1 Gennaio 2021 – 29 Febbraio 2024

With SLICES-SC, we aspire to foster the community of researchers around this ecosystem, create and strengthen necessary links with relevant industrial stakeholders for the exploitation of the infrastructure, advance existing methods for research reproducibility and experiment repeatability, and design and deploy the necessary solutions for providing SLICES-RI with an easy to access scheme for users from different disciplines. A set of detailed research activities has been designed to materialize these efforts in tools for providing transnational (remote and physical) access to the facility, as well as virtual access to the data produced over the facilities. The respective networking activities of the project aspire in fostering the community around these infrastructures, as well as open up to new disciplines and industrial stakeholders.

Social Explainable AI (SAI)
1 Febbraio 2021 – 31 Luglio 2024

SAI will develop the scientific foundations for novel ML-based AI systems where (i) each individual is associated with its own “local AI twin” (called Personal Data Ecosystem, PDE), which acts as the individual’s proxy in a complex ecosystem of interacting PDEs; (ii) PDEs elaborate local data via explainable AI models tailored to the specific characteristics of their human peers; (iii) PDEs interact with each other to build more complex global AI models and/or come with collective outcomes built on the local models; (iv) interaction between local PDEs is driven by (quantifiable) models of the individual and social behaviour of their human peers; (v) quantifiable human behavioural models coupled with complex network analysis makes the global AI models and outcomes explainable-by-design. The ultimate goal of SAI is thus to provide the foundational elements enabling a collective of distributed explainable AI PDEs to create, via a human-centric approach, global AI models whose processes and outcomes are explainable and tailored to the needs and constraints of individual users. The interactions between PDEs in SAI will be engineered to preserve the plurality of information inherent in the data, giving them all the elements to take informed decisions and avoid biases, or, at least, to transparently expose biases inherent in data and in the decision process.

Pitem Pa.C.E. – Far Conoscere
Far conoscere (Faire connaitre) si propone, tramite il censimento, la digitalizzazione e la successiva valorizzazione del patrimonio culturale materiale e immateriale, di realizzare percorsi tematici, legati a varie epoche storiche, per fare emergere le specificità e le attrattività dei territori dell’area ALCOTRA.