Laboratorio di Ingegneria dei Dati — a research laboratory at Roma Tre University, Department of Civil, Computer Science and Aeronautical Engineering.
At LID, we lift the lid on data and applications: making them transparent, accessible and secure. Transparent, so that how an AI system reaches its conclusions can be understood and checked, not simply taken on faith. Accessible, so that raw, scattered information can be turned into something applications, researchers and organizations can actually put to use. Secure, so that the systems built on that data can detect and withstand attacks, not just process them.
Data are not just tools — they are strategic resources for a more connected, secure and sustainable world.
The Data Engineering Laboratory (LID) is a reference point for advanced research and innovation in data management and data-centric AI, with a focus on data-driven innovation and next-generation technological solutions. LID develops methods, tools and frameworks that tackle the most complex challenges of the digital society, placing data at the heart of its research and applied activities.
Our mission is to promote an integrated, interdisciplinary approach to data management, aimed at technologies that improve the accessibility, usability and security of data — for the benefit of public and private organizations and society at large. Through decades of national and international collaboration with academic, industrial and institutional partners, LID operates as an open, collaborative innovation hub.
ERC panels PE6_5, PE6_7, PE6_10 — Computer Science & Informatics, within Physical Sciences and Engineering.
Innovative methods that harness data to enable new business models, sharpen decision-making and optimize operational workflows — boosting competitiveness and sustainability across sectors.
AI systems built around the data that feeds them, able to learn from heterogeneous, unstructured or large-scale datasets — with a focus on efficiency, reliability and explainability.
Solutions that harmonize, consolidate and verify data from disparate and heterogeneous sources, ensuring the consistency, accuracy and utility needed for sound decision-making.
Advanced ML techniques for extracting knowledge from unconventional sources — documents, historical archives, manuscripts, audio and video — applied to digital humanities, cultural heritage, healthcare, smart cities and business intelligence.
Tools and protocols for data protection, from intrusion detection to automated response, combining machine learning with real-time monitoring to keep digital infrastructures resilient.
A multidisciplinary team of researchers and developers, connected to national and international networks, translating data into real value — for the economy, institutions and communities.
Based in the Department of Civil, Computer Science and Aeronautical Engineering, Roma Tre University.
The team also grows with a variable number of scientific collaborators and developers, who join LID on specific projects.
Leading researchers who have visited LID in recent years, sharing their work and helping shape our research directions.
A selection of the projects LID has led or contributed to in recent years.
The full record of recent years spans several topics, including: data provenance and integration; data-centric AI and data augmentation; entity resolution; knowledge graphs and link prediction; large language models and agentic AI; explainable AI and fairness; OCR and document analysis, including historical handwritten manuscripts; speech processing; cybersecurity, intrusion response and blockchain-based resilience — sourced from DBLP.
Part of established regional research infrastructures, with an active track record of collaboration with public and private partners.
Member of the Distretto Tecnologico Beni e Attività Culturali del Lazio, connecting research on cultural heritage and AI.
Part of the regional innovation ecosystem linking universities, research centers and enterprises across Rome and Lazio.
Collaborations with industrial partners in the ICT sector, from applied research to joint technology transfer initiatives.