Center for Artificial Intelligence and Data Science


    CAIDAS is JMU's interdisciplinary research center in the field of Artificial Intelligence and Data Science, where research questions in Machine Learning, Data Science, Image and Text Analysis, AI Systems, Ethics/Legal/Societal Acceptance, and Economy and Transfer are to be answered in particular within the four central application pillars: AI for (Life) Science, Human-Centered AI, AI in Digital Humanities, Economics/Law and AI. The methods for these applications are also researched at CAIDAS in the underlying area Foundations of AI and Data Science.

    AI for (Life) Sciences

    Application and development of AI techniques to improve research and understanding in the field of life sciences, including healthcare, biology, and geography.

    • Super Resolution
    • Quantitative Single-Cell Biology
    • Environmental Science
    • Medical Data Analsysis
    • Remote Sensing


    Human-Centered AI

    Focus on developing AI systems that effectively collaborate with humans, including studies on human-AI interaction, explainability of AI decisions, and AI integration in society.

    • Human-AI Interaction
    • Computational Social Sciences
    • AI in Software Engineering
    • Democratizing Language Technology
    • Recommender Systems


    AI in Digital Humanities

    Application of AI techniques to study and enhance various aspects of human culture and history, such as literature, music, language, historical documents and other cultural heritage.

    • Computational Literary Studies
    • AI in Musicology
    • Geolingual Studies
    • Multilingual NLP
    • Digitization of Cultural Heritage


    Economics/Law and AI

    Application of AI in business, industry and law with a focus on improving efficiency, sustainability and decision-making.

    • AI Adoption in Organizations
    • Smart Cities &  Urban Mobility
    • Smart Industry & Logistics
    • Future Energy Systems
    • AI in Law
    • Fraud Detection


    Foundations of AI and Data Science

    CAIDAS also conducts research on the fundamentals on Machine Learning and Data Science, developing methods and techniques that can be used in all of the application pillars. The main fundamental research areas are Deep Learning, Representation Learning, Reinforcement Learning, Statistical Learning, Machine Learning for Complex Networks, Computer Vision, Natural Language Processing, Pattern Recognition.


    Principal Investigators

    Ingo Scholtes

    Machine Learning for
    Complex Networks

    Dominic Grün

    Computational Biology of Spatial Biomedical Systems

    Carlo D'Eramo

    Reinforcement Learning and Computational Decision Making

    Christof Weiß

    Computational Humanities

    Goran Glavaš

    Natural Language

    Gunther Gust

    Process and IT integration for
    AI in the company

    Hannes Taubenböck

    Global Urbanization and
    Remote Sensing

    Radu Timofte

    Computer Vision

    Andreas Hotho

    Data Science

    Frank Puppe

    Artificial Intelligence and Knowledge Systems

    Marc Latoschik

    Human-Computer Interaction

    Fotis Jannidis

    Computational Philology and Modern German Literary History

    Carolin Biewer

    English Linguistics

    Christoph Flath

    Information Management

    Frédéric Thiesse

    Business Informatics and Systems Development

    Eric Hilgendorf

    Information and Computer Science Law


    Theory of
    Machine Learning


    Mathematics of
    Machine Learning


    Pattern Recognition


    Artificial Intelligence for the Molecular Sciences


    AI in Computational and Theoretical Biology

    Further appointment procedures are in preparation.