| Opis zakresu działań | The research interests of the team cover four aspects: modelling, exploration, optimisation and workflows.
Modelling – building formal representations of real-world objects and processes. This field involves formal modelling of IT systems using, among others, various classes of Petri nets, specialised formal languages (e.g. Alvis) and finite automata. Its goal is to create precise, mathematically-grounded models, enabling the analysis of system correctness, security, and performance, using tools such as full and reduce state spaces, symbolic analysis, model checking techniques, as well as model reduction and structural analysis.
Exploration - examination of the data for its understanding, detection of patterns and dependencies, and preservation of significant details. The field entails the exploration of data and knowledge in large, heterogeous datasets. The research involves relational and graph databases, blockchain as well as analysis of spatial (GIS), text and image data, using machine learning, computer vision, text analysis (using LLMs and VLMs) as well as pattern detection, anomaly and dependency detection techniques.
Optimisation – improvement of processes using results of previous analyses. Works in this field involve optimisation of structures, processes, and algorithms in IT systems and data analysis. These cover optimisation of formal processes as well as of data exploration algorithms, decision processes, and machine learning models.
Workflows – ordering and understanding of research and analytic processes. This field covers process mining, integration of process data with formal models, and design of complex workflows used to join modelling, exploration, and optimisation. The goal here is to create coherent, repeatable and automatable pipelines for research and data analysis. |
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Ernst SebastianFaculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering