• Learning and deploying safe and trustworthy models of data provenance

    Project ID: STAI-CDT-2023-KCL-21
    Themes: AI Provenance, Logic
    Supervisor: Albert Meroño Peñuela, Luc Moreau

    Our modern lives are increasingly governed by ubiquitous AI systems and an abundance of digital data. More and more products and services are providing us with better tools and recommendations for our professional,...

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  • Trusted Collective Intelligence through Norms, Ontologies and Provenance

    Project ID: STAI-CDT-2023-KCL-12
    Themes: AI Provenance, Norms
    Supervisor: Elena Simperl, Dr Timothy Neate

    Collective intelligence (CI) communities are among the greatest examples of collaboration, capability, and creativity of the digital age. CI communities allow large groups of individuals to work together towards a shared...

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  • Creating and evolving knowledge graphs at scale for explainable AI

    Project ID: STAI-CDT-2022-KCL-1
    Themes: AI Provenance, Argumentation, Verification
    Supervisor: Prof Elena Simperl

    Knowledge graphs and knowledge bases are forms of symbolic knowledge representations used across AI applications. Both refer to a set of technologies that organise data for easier access, capture information about people,...

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  • Trustful Ontology Engineering and Reasoning through Provenance

    Project ID: STAI-CDT-2021-KCL-12
    Themes: AI Provenance, Logic
    Supervisor: Albert Meroño Peñuela

    Ontologies have become fundamental AI artifacts in providing knowledge to intelligent systems. The concepts and relationships formalised in these ontologies are frequently used to semantically annotate data, helping...

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