Mateusz is a PhD student at Poznan University of Technology and IDEAS NCBR. His primary research focuses on causality, particularly causal discovery using both deep learning methods and approaches designed for small sample sizes. He is currently investigating how to bridge the gap between theoretical causal discovery and real-world applications by examining statistical assumptions in practical datasets.
His research interests also extend to explainability in machine learning, with a particular focus on game theory-based methods. Mateusz is exploring how to make these methods better align with human intuition, making AI systems more transparent and trustworthy.
In his free time, he enjoys running and hiking.
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