Jerzy Stefanowski

Jerzy Stefanowski is a Full Professor at the Institute of Computing Science, Poznan University of Technology. He specializes in Machine Learning, Data Mining, and Knowledge Discovery, with a focus on imbalanced data, data streams, and explainable AI. His research addresses challenges in classifier learning from skewed datasets and has led to contributions like the BRACID algorithm. He has supervised multiple PhD students and holds grants such as the NCN-funded project on imbalanced data (2014–2017). A corresponding member of the Polish Academy of Sciences and Editor-in-Chief of the journal Foundations of Computing and Decision Sciences, he has organized numerous conferences and workshops in AI and data mining.

Education:

• M.Sc./Eng. in Control Engineering (1987)
• Ph.D. in Computer Science (1994)
• Habilitation Thesis (2001)

Research Interests: Machine learning, data streams, imbalanced classification, rough sets, medical informatics, and interpretable AI. His work emphasizes overcoming algorithmic biases in imbalanced datasets and developing robust classification strategies.

Awards: Includes recognition from the Polish Information Processing Society, Foundation for Polish Science, and the Polish Academy of Sciences. He has also received medals and grants from national educational bodies.

Grants: Led projects such as Learning Classifiers from Imbalanced and Evolving Data (NCN, 2014–2017) and Algorithms Transforming Data Representation for Machine Learning Systems (KBN, 2004–2007).

Labs/Teams: Leads the Machine Learning Group at Poznan University of Technology and chairs the Scientific Council of the Institute of Computer Science, Polish Academy of Sciences.