The Institute of Applied Computer Science at the Jagiellonian University conducts interdisciplinary research in computer science, combining theoretical foundations with practical applications. Key areas include the development of intelligent learning systems, data and knowledge mining, interactive systems for visual design (including graph transformations and evolutionary algorithms), touchless interfaces (BCI), serious games, GPU programming, finite element modeling (FEM), automatic hp-adaptation algorithms, and applications of computer science in bioinformatics, medicine, and biochemistry. Thanks to its interdisciplinary approach and collaboration with other scientific units, IIS UJ bridges the gap between theoretical computer science and its practical applications in science and industry.
Scientific activity is carried out across various departments, each focusing on specific research areas.
The research topics include:
- graph transformations,
- evolutionary algorithms,
- innovative computer-aided engineering design,
- evaluation/classification of designs based on graph structures,
- visual languages and reasoning in design,
- automatic hp-adaptation algorithms.
More information can be found on the Department of Design and Computer Graphics website (PL).
The scientific interests of the Department's staff include topics such as touchless interfaces (BCI), GPU programming, serious games, HCI, as well as interdisciplinary areas at the intersection of computer science and the humanities, such as ludology, pop culture theory, software studies, and cybertextuality. The Department of Human-Centered Artificial Intelligence is a member of the European Game Academy and part of the Viking project.
More information can be found on the Department's website.
The main goal of research conducted in the Department of Information Technology is the development of intelligent IT systems capable of learning, knowledge acquisition (Data Mining), and knowledge generation (Knowledge Mining), along with their practical application in solving real-world problems.
Research areas include:
- applied data analysis,
- machine learning,
- pattern recognition,
- knowledge acquisition and generation,
- random networks,
- biometrics,
- intelligent systems in bioinformatics.
The methods developed at the Department of Information Technology and the systems that implement them are experimentally used to solve a wide range of scientific and business problems. We are particularly interested in applications in bioinformatics, medicine, and biochemistry.
More information can be found on the Department of Information Technology website.
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