Industrial Informatics Department

The Industrial Informatics Department (IID) is a well-established research group both at the Faculty of Electrical Engineering (FEL) and the Czech Institute of Informatics, Robotics and Cybernetics (CIIRC) at the Czech Technical University in Prague (CTU). The department unites two closely connected research groups — Optimization and Embedded Systems — forming a strong, interdisciplinary team. The department focuses on theory in informatics as well as the transfer of research knowledge into industrial practice. Our research results are documented in numerous papers published in top-tier scientific journals and conference proceedings. The list of our industrial partners, the list of projects, and the industrial awards we have obtained illustrate our successful applied results. The vision of the department is to strengthen cooperation among research groups from any faculty or university to support research activities for industry.

The Optimization group specializes in advanced methods of combinatorial optimization, scheduling, planning, and artificial intelligence. The group develops exact and heuristic algorithms to solve complex decision-making problems. The group’s research ranges from classical operations research techniques to modern AI- and machine learning–enhanced approaches. These approaches enable more efficient modelling, prediction, and optimization in dynamic environments. We apply our methods to production, robotics, healthcare, human resources management, energy production, embedded systems, communication protocols, military systems, logistics, and more. We are open to exploring new areas.

The Embedded Systems group focuses on real-time, safety-critical, and high-performance embedded computing. The group develops methods that ensure the predictable and reliable behaviour of complex cyber-physical systems. The group’s research covers real-time scheduling, operating systems, formal verification, and model-driven engineering, and it is increasingly incorporating AI and machine learning techniques. The group addresses challenges related to heterogeneous and many-core platforms, industrial communication, autonomous systems, robotics and automotive electronics. Our application areas include automotive, aviation, safety, and security.