All 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.

  • Applied Informatics Group

    Team leader
    Arkadiusz Sochan

    The Applied Informatics Group was established in 2022 with the aim of enhancing the efficiency of commercialization of technologies developed at Institute. It supports other teams within the Institute in the area of applied informatics during the preparation and implementation of projects, as well as when transferring results to the business environment. In particular, it estimates the time and resource requirements of planned tasks and prepares software prototypes and demonstrators. The team also maintains the Institute's ICT infrastructure.

  • Security, Modelling and Performance Evaluation Group

    Team leader
    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
    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
    Przemysław Głomb

    Zespół Uczenia Maszynowego specjalizuje się w zagadnieniach projektowania i doboru algortymów i modeli uczenia maszynowego do projektów aplikacyjnych, przede wszystkim związanych z wizją komputerową i szeregami czasowymi. W Zespole prowadzone są również badania podstawowe z obszaru metod uczenia maszynowego w obrazowaniu hiperspektralnym, a ostatnio przede wszystkim związane z uczeniem głębokim -- zagadnienia ,,martwych neuronów'', continual i reinforcement learning. Wywodząc się z Zespołu Systemów Multimedialnych, członkowie zespołu mają duże doświadczenie z zakresu analizy/drążenia danych (m.in. obrazy hiperspektralne, dane biomedyczne, obrazy 3D, dane sygnałowe), metod przetwarzania (m.in. statystyczne klasyfikatory, architektury uczenia głębokiego) jak i technicznych/organizacyjnych aspektów realizacji projektów badawczych i wdrożeniowych (m.in. proces przygotowania i wsparcie wdrożenia systemów uczenia maszynowego dla konkretnych problemów).