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Objective

Our research aims to analyse how artificial intelligence can be used in practice. This divides our research into three parts: A computer science part, in which we develop and extend machine learning models to serve the needs of users; a human computer interaction part, in which we study how users interact with machine learning models and what makes them build trust in the models; and a practical part, in which we study the benefits that AI models can have in various domains.

Projects

  • White-Box AI

    Transparent decision support through interpretable machine learning models

  • ClimateBert

    Make Climate Risk understandable

  • Headwind

    A Hypoglycaemia Warning System for the Prevention of Road Traffic Accidents
    Background

White-Box AI

Transparent decision support through interpretable machine learning models

ClimateBert

Make Climate Risk understandable

Headwind

A Hypoglycaemia Warning System for the Prevention of Road Traffic Accidents
Background

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