Research networks, consortia and teams

The theoretical foundations of computer science research team specializes in the study of fragments of first-order logic, particularly focusing on two-variable fragments, logics with transitivity, and counting mechanisms. The team’s research focuses on the problems of decidability and satisfiability in various logic fragments, such as guarded logic and fluted fragments. An important part of the team’s work is to analyze the impact of adding certain features, such as transitivity or semantic constraints, on the complexity and decidability of these logics. The team also studies the limits of decidability and theoretical aspects of computational complexity in the context of logic applications in computer science.

Lidia Tendera, Ph.D prof. UO – research team leader
Prof. Aleksander Ivanov, Ph.D
Prof. Ian Pratt-Hartmann, Ph.D
Dariusz Marzec, M.Sc. (Ph.D. student)
Zbigniew Bonikowski, Ph.D
Andrzej Jasinski, Ph.D

The Unification in Modal Logics research team conducts research on the theoretical aspects of unification in various modal logics, with particular emphasis on transitive logics and locally arrayed logics. Their work also includes research on the theoretical framework for the fusion of modal logics, which allows for a better understanding of the structure and properties of these systems. The team also explores implicate fragments of fuzzy logics and asymptotic comparisons of these fragments, with the aim of investigating differences and similarities in the logical behavior of these systems. In their research, they combine both theoretical approaches and practical applications, which allows them to develop new methods and tools in the area of unification in modal logics.

Barbara Morawska, Ph.D – team leader
Sławomir Kost, PhD
Dariusz Marzec, M.Sc. (Ph.D. student)

The Operating Systems and Artificial Intelligence research team focuses on research into the application of AI in optimizing and managing computer systems. Key areas include the development of artificial intelligence algorithms for monitoring and assessing the health of infrastructure, which has applications in managing operating systems resources. In addition, the team is exploring advanced cryptographic methods that integrate with operating systems to enhance data security in these environments. The team’s work also includes the optimization of wireless networks, where AI assists in routing management, leading to longer sensor network life. All these activities are aimed at creating intelligent, secure and efficient operating systems.

Mariusz Pelc, Ph.D., UO professor – research team leader
Slawomir Stemplewski, D.Sc.
Piotr Dzierwa, Ph.D.
Aasam Abdul Karim, PhD
Michał Szczerba, M.Sc.
Zbigniew Lipiński, PhD
Patryk Mendoń, M.Sc.
Marcin Szymanek, M.Sc. (Ph.D. student)

The IT Security research team conducts advanced research on the protection of IT systems, with a particular focus on the security of mobile business applications, IoT networks and cryptography. Their work includes analyzing the threats posed by the reuse of cryptographic keys in IPsec IKE protocols, as well as studying the stability of positive systems in IoT network gateways. The team is also analyzing the vulnerability of IoT devices to cyber attacks using the Naive Bayes classifier, developing methods to optimize packet management in IP routers using rough set theory. In their research on mobile botnets and multi-stage attacks, the team is developing tools for modeling and assessing the impact of vulnerabilities, with the goal of making systems more resilient to cyber threats.

Adam Czubak, Ph.D. – research team leader
Jarosław Kobiela, Ph.D
Michał Podpora, Ph.D., UO professor
Piotr Urbaniec, PhD
Tomasz Machalewski, M.Sc. (Ph.D. student)
Jolanta Tańcula, Ph.
Marek Barycki, M.Sc. (technical pr.)

The Optimization, Approximation and Game Theory and Their Applications research team focuses on developing advanced data mining techniques and their practical applications in analyzing user behavior and optimizing processes in information systems. In its research, the team applies machine learning methods to classify user sessions in e-commerce, identify web bots and analyze the performance of web applications. Optimizing the behavior tree in RTS games and solving scheduling problems using goal-seeking techniques are also important areas of research. The team is also exploring the use of information theory-based algorithms for discovering user profiles, which supports personalization and efficiency in digital environments. Their work aims to improve the reliability and efficiency of data mining systems, which has applications in areas such as e-commerce, network security and optimization of business decisions.

Gleb Polevoy, Ph.D, Prof. UO – research team leader
Grażyna Suchacka, Ph.
Jacek Iwański, Ph.
Andrzej Kozik, M.Sc.
Mariusz Marek, M.Sc.
Sebastian Bala, Ph.D