Organisation: Interdisciplinary Centre for Security, Reliability and Trust (SnT)

  • News

    Microsoft’s LINGUA initiative selects Luxembourgish to strengthen AI inclusion

    Microsoft announces the awardees of its LINGUA Open Call. Among the selected projects is LuxVLD led by the University of Luxembourg’s Interdisciplinary Centre for Security, Reliability and Trust (SnT). LuxVLD will create high‑quality datasets to support AI systems in Luxembourgish.

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  • News

    Seeing what usually stays invisible: Meet Thomas

    Meet Thomas Feuillen: a Belgian researcher whose unexpected COVID-era detour led him to SnT where he entered the world of radars.

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  • Research Groups

    People

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  • Research Groups

    2026 Summer School on Integrated Sensing and Communications: A Sensing Centric Approach

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  • Research Projects Pages

    Geophysical and Extraterrestrial Observations for Safety, Protection, Awareness, and prevention of Critical Effects (GEOSPACE)

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  • Core Research Projects

    Geophysical and Extraterrestrial Observations for Safety, Protection, Awareness, and prevention of Critical Effects (GEOSPACE)

    The GEOSPACE project focuses on the study of variable geospace conditions and their potentially adverse effects on critical space- and ground-based infrastructure.

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  • News

    Can DNA research teach us how to test web applications better?

    What does DNA have to do with web application testing? A research team in Luxembourg is using bioinformatics techniques to detect hidden user behaviour patterns and prevent problems before they appear. 

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  • News

    Teaching robots to work with humans

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  • News

    Collaborative drone swarms for airspace protection

    What happens when dozens or even hundreds of drones work together? Researchers are tackling this challenge as drone intrusions become more sophisticated. With AI the team is developing methods that enable coordinated drone swarms to respond to complex aerial threats.

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  • News

    When choosing the wrong AI setup becomes a costly mistake 

    What if launching powerful AI models became simple and affordable? Researchers are exploring practical ways to help companies navigate AI deployment with more clarity and fewer costly mistakes. 

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