Associated Professor in the Institute of Computer Science at the University of Silesia in Katowice. The guest editor of the Special Issue "Knowledge Engineering and Data Mining" and author of over a hundred scientific papers on artificial intelligence and machine learning. A chairwoman of invited sessions at international conferences related to Knowledge Engineering and Data Mining. A supervisor of three doctoral students in computer science and a regular reviewer of highly cited journals related to the artificial intelligence area. During 2012-2015 the head of the grant "Exploration of rule-based knowledge bases" National Science Center. Since 2020 the Deputy Dean of the Faculty of Science and Technology for Promotion and Development. 

Since 2021 a coordinator of the "Monday with IT" program, which aims to organize regular online meetings (lectures, workshops) with the most popular and most interesting companies in the IT branch dedicated to the Faculty of Science and Technology students. 

Her research interests are related to unsupervised learning methods, especially outlier detection algorithms. Outlier detection algorithms identify anomalous data points that deviate significantly from the majority of a dataset, using techniques such as statistical methods, clustering, and machine learning models. They are crucial in machine learning because outliers can distort model training, leading to inaccurate predictions, and their detection is essential in applications like fraud detection, network security, and data cleaning.