Informatics Engineering

Research Topic Summary.

The topic is relevant because assessing the cyber resilience of IoT is a complex problem due to the heterogeneity of the IoT ??environment, the large number of different components and protocols, especially due to the threats of quantum computing. The life cycle of IoT systems is long and complex: industrial and medical IoT devices have been in use for decades. The transition to hybrid systems, quantum-safe cryptography (Post-Quantum Cryptography, PQC) is slow and complex. It is necessary to identify the most vulnerable devices and protocols as soon as possible. Penetration testing of IoT systems, using the capabilities of artificial intelligence, is a promising way to solve this problem. Penetration testing of IoT systems (penetration testing, pentest) differs from traditional IT systems, is complex due to the heterogeneity of the IoT ??environment, the large number of different components and protocols. A realistic transition to quantum security requires hybrid cryptosystems (using PQC together with traditional cryptography). The dissertation would investigate how these hybrid systems operate in resource-constrained IoT environments and whether they themselves create new traditional vulnerabilities (e.g., excessive energy consumption or slow connection establishment leading to DoS attacks).

Research Topic Summary.

This project targets reliable separation of transparent and mirror-like objects in industrial scenes, where conventional vision often fails due to reflections and unreliable depth. We will develop a real-time method that fuses color, depth, and polarization cues, grounded in the physical laws of refraction and reflection. A reference demonstrator will be built to run on local computing devices and integrate with a robotic gripper or conveyor line. Evaluation will cover not only accuracy and false-alarm reduction, but also latency, processing throughput, energy consumption, and robustness across different sensors. The outcome is open-access software and clear deployment guidelines (illumination setup, sensor selection, calibration) that improve quality inspection accuracy, reduce downtime, and enhance operational safety.

Research Topic Summary.

We are creating a new generation of artificial intelligence by combining data science with fundamental laws of physics. Traditional AI systems learn only from data, which requires enormous resources and sometimes leads to errors or illogical solutions. Our hybrid method has "taught" AI to understand basic rules. This allows us to develop AI platforms that operate significantly faster, require less data, and make better, safer, and more physically realistic decisions. If you are not afraid of difficulties and challenges, join us in our efforts to create more reliable autonomous systems (e.g., https://www.youtube.com/watch?v=DvgsmHiadhQ), smarter robots, and a more efficient industry.

Research Topic Summary.

The topic strengthens cyber resilience of digital ecosystems using a risk based assurance methodology across the full lifecycle. It blends threat modelling, supply chain vetting, resilience metrics and governed recovery to help organizations withstand incidents and recover faster. The outcome practical guidelines and demonstrators for business, public sector and industry.

Research Topic Summary.

The project aims to develop a personalized, non-invasive system for assessing glucose trends from finger optical signals and detecting high-risk episodes, reducing the need for frequent finger pricks. An optical probe with multi-wavelength emitters and a photodiode will be built, with integrated temperature and contact-pressure sensing and a stable mechanical holder. Software will handle signal-quality control, artifact suppression, and uncertainty estimation, while personalized learning will use participants’ reference measurements. Evaluation will cover trend-error, episode detection, latency, throughput, and energy consumption. The outcome is a working prototype, open-access methods, and clear deployment guidelines.