90
Employees
80
Publications in 2024
53
Projects
The accelerating global adoption of artificial intelligence (AI), data-driven technologies and increasingly complex software systems presents both profound opportunities and significant challenges. Organizations must navigate evolving legal frameworks like the EU AI Act, ensure the development and deployment of ethical and trustworthy AI, manage fragmented data ecosystems and foster effective collaboration between humans and AI. These demands underscore the need for robust methodologies, validated tools and practical expertise to guide the responsible and effective integration of these transformative technologies into society and industry, while addressing the critical need for human upskilling and adaptability in this digital age.
The Human-centred AI, Data and Software unit enables public and private organizations to successfully navigate this complex digital transformation. Its mission is to advance human-centred artificial intelligence, data science and software engineering by fostering innovations that improve human-AI collaboration, ethical AI development and trustworthiness. The unit empowers industry and society through cutting-edge research and technology, enabling sustainable growth, enhanced human capabilities and ethical AI adoption across multiple sectors.
To achieve its mission, the unit integrates multidisciplinary expertise across five research groups:
Through these combined strengths, the Human-centred AI, Data and Software unit is driving impactful innovation in AI, data and software, shaping a future in which technology serves humanity effectively and responsibly.
AI for Space Objects Detection 2
A collaborative 3D Explosive Ordnance reference database
COllaborative design in MIXed-presence interactive Spaces
CLERK: A Companion Large Language Model Expert for modeling Regulatory Knowledge
Mercado J.S., Ma Q., de Kinderen S., Winter K., Cabot J.
Data and Knowledge Engineering, vol. 164, art. no. 102578, 2026
Reconciling Urban Mobility and CCAM Digital Twins for Enhanced Integration and Mutual Advancement
Feltus C., Ferrero F., Nicolas D., Viti F., Castignani G., Connors R., Khadraoui D., Nakao H.
Data Science for Transportation, vol. 8, n° 1, art. no. 4, 2026
Semantic drift evaluation in language and data-specific digital twin frameworks
Abbasi F., Pruski C., Sottet J.S.
Future Generation Computer Systems, vol. 177, art. no. 108240, 2026
