Research Group
Matej Kloska
Research areas: machine learning, anomaly detection
Position: Research Engineer
Matej is a research engineer focused on anomaly detection using a statistical approach emphasizing model explainability and human-in-the-loop. He worked on multiple projects in the energy domain and is interested in developing environmentally friendly solutions for the future.
Matej holds a master’s in Intelligent Software Systems from the Faculty of Informatics and Information Technologies STU. After graduating, he worked in two international companies where he applied his knowledge in data engineering and further strengthened his industry knowledge of data engineering management. In 2023, he defended his PhD thesis in knowledge-based anomaly detection.
Selected Projects
Selected Publications
Towards Symbolic Time Series Representation Improved by Kernel Density Estimators
Kloska, M., Rozinajova, V. This paper deals with symbolic time series representation. It builds up on the popular mapping technique Symbolic Aggregate approXimation algorithm (SAX), which is extensively utilized in…