Research Teams

  • Computer Vision Systems Group

    Team leader
    PhD Krzysztof Domino
    The Computer Vision Systems Group conducts research on advanced computer vision methods, multimodal data analysis, and decision support systems, developing solutions for complex transport, environmental, and diagnostic systems. An important aspect of the group’s activity is international scientific collaboration and participation in research projects, including the Horizon Europe Q-Fence project focused on secure data processing using post-quantum cryptographic methods.

  • Security, Modelling and Performance Evaluation Group

    Team leader
    PhD, D.Sc. Joanna Domańska

    Systems Modelling and Performance Evaluation and Security Group (SMaPESG) conducts research on models of computer systems and novel methods of modelling. In the scope of interests of the Group there are mainly models of computer networks. We are engaged in simulation and analytical modelling, both queuing models and other methods. Our experience embraces using of well-established modelling packages, like NS, OmNET++ or PRISM as well as creation of advanced proprietary software working in parallel environments.

  • Internet of Things Group

    Team leader
    DSc Krzysztof Grochla

    Our team specializes in Internet of Things (IoT) research, with emphasis on wireless communication and network protocols. We design and analyze the performance of network protocols, address issues related to interoperability, and the semantic description of data and operation of IoT systems. In addition, we investigate auto-configuration, energy consumption minimization, and localization in embedded devices.

    We specialize in:

  • Machine Learning Group

    Team leader
    PhD Przemysław Głomb

    The Machine Learning Group specializes in the design and selection of machine learning algorithms and models for application projects, primarily those related to computer vision and time series. The team also conducts basic research in the field of machine learning methods for hyperspectral imaging, and recently has focused primarily on deep learning—specifically, issues related to “dead neurons,” continuous learning, and reinforcement learning. Originating from the Multimedia Systems Group, the team members have extensive experience in data analysis and mining (including hyperspectral images, biomedical data, 3D images, and signal data), processing methods (including statistical classifiers and deep learning architectures), as well as the technical and organizational aspects of carrying out research and implementation projects (including the process of preparing and supporting the implementation of machine learning systems for specific problems).