Ordsky med fokus på "Explainable AI", der de mest fremtredende ordene inkluderer 'Explainable', 'AI', 'Human Understanding' og 'Global Explanation'. Andre viktige begreper er 'Transparency', 'Interpretability', 'Ethical AI' og 'Local Explanation'. Bakgrunnen har en blå fargegradient fra mørk øverst til lys nederst."
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Trustworthy and Efficient Transfer Learning AI (TETRA AI) is a research group dedicated to advancing methods that make AI models both trustworthy and highly efficient.

About the research group

  • Research areas

    The group focuses on developing novel techniques such as low-rank approximation to reduce model complexity and computational cost, while injecting formal domain knowledge to enhance transparency, robustness, and trustworthiness. TETRA AI’s research enables zero-shot and few-shot learning, empowering models to adapt reliably to new tasks with minimal labeled data. The team’s mission is to create trustworthy, resource-efficient AI systems that can be confidently deployed in real-world, high-stakes environments.

Members

  • Scientific staff
  • PhD candidates and post doctors
    • External partners and PhD candidates
      • Univ.-Prof. Dr.-Ing. Kyandoghere Kyamakya
        https://www.aau.at/en/team/kyamakya-kyandoghere/
      • Univ.-Prof. Dr. Martin Gebser
        https://www.aau.at/en/aics/research-groups/research-group-production-systems/team/martin-gebser/
      • Ali Deeb (stipendiat)
      • Vianney Kambale (stipendiat)

Projects

Publications: Transfer Learning

Publications: Trustworthy AI, Explainable AI, and Knowledge-Infused Learning

Publications: Robust and Generalizable Neural Architectures for Knowledge Extraction