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  • Research Profile

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    Campus der Universität Bielefeld
    © Clara Wrede

Research Profile

The CoR-Lab offers interdisciplinary competencies that address research questions on the working world of the future from the perspectives of computer science, psychology, sociology and economics in a goal-oriented and cooperative manner. Together with partners from industry and the service sector, CoR-Lab scientists work closely together to develop solutions that are then applied and evaluated in practice. In the following, we introduce you to the professors and working group leaders currently active in the CoR-Lab and their competencies. The links will provide you with more detailed information on the profiles of the participating working groups.

Selected Projects

    © Bielefeld University, S.Jonek


    In the EU project VEDLIoT, IoT devices are developed based on Deep Learning methods to make them more powerful and energy efficient.

    Funded by EU Horizon 2020, No.: 957197

  • CoSMo
    © Bielefeld University


    In the COVR EU AWARD project CoSMo, methods for efficient proof of safety of collaborative human-robot applications are developed.

    Funded by EU-Horizon 2020, No.: COVR 12341234.2

  • CogIMON


    CogIMON investigates interactions that require active and adaptive regulation of both human and robot motion and behavior.

    Funded by EU-Horizon 2020, ICT No.: 644727.

  • AI4DG
    © pixabay


    In AI4DG, a decentralized AI platform is being developed that enables secure and autonomous control of distribution grids with a high share of RE.

    Funded by the BMBF, FKZ.: 01IS21101A

    © Bielefeld University


    Construction of a verifiable electronic assembly, from production and commissioning to the end of the operating phase, applicable in critical infrastructures.

    Funded by the BMBF, FKZ.: 16ME0276

  • Arbeitswelt plus


    The competence center bundles know-how and experience from science and industry in association with trade unions on the topics of AI and Work 4.0.

    Funded by the BMBF, FKZ.: 02L19C104

  • ITS.ML


    The BMBF-funded ITS.ML project is concerned with the use of machine learning methods for intelligent technical systems of the next generation.

    Funded by the BMBF, FKZ.: 01IS18041A

  • EML4U
    © pixabay


    Method development in the area of explainability and transparency of ML and research of central questions for episodic, interactive learning.

    Funded by the BMBF, FKZ.: 01IS19080A

  • itsowl RPTTrans
    © Jansen & Fechtelpeter, it’s owl

    it's owl RPTTrans

    The working group contributes to the digital innovation platform and carries out transfer pilots with medium-sized companies as case studies.

    Funded by the MWIDE NRW, FKZ.: 005-2011-0036

  • iAtA
    © pexels


    Realization of a digital extended reality assistance system (XR), to improve the technical training of junior staff.

    Funded by the MKW NRW, FKZ.: 005-2011-0241

  • InSensEPro
    © CLAAS KGaA mbh


    The aim of the project is to optimize the efficiency of the harvest. A sensor network will monitor machine processes and interpret them using AI.

    Funded by the MWIDE, FKZ.: 005-2001-0028

  • ML4PRO²
    © it's owl


    The aim of the ML4Pro² project is to make the latest machine learning (ML) methods sustainably available for intelligent products and production processes.

    Funded by the MWIDE, FKZ.: 1807ow003a

Selected Publications

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