Research activities focus on data science, artificial intelligence and machine learning, with a particular focus on the development of intelligent systems that are able to analyse complex data and support decision-making.

The main research areas include anomaly detection, explainable artificial intelligence, time series analysis, cybersecurity, industrial control systems, and the study of energy-efficient network infrastructures. The work aims to develop methods that can detect unusual patterns, evaluate the performance of models with limited or missing labeled data, and explain why a system identifies certain behaviors as abnormal.

The research combines theoretical model development, experimental evaluation and validation in real-world applications, especially in environments where reliable, transparent and practical AI solutions are needed.