Paweł Zyblewski

Dr. Paweł Zyblewski is an Assistant Professor in the Department of Computer Systems and Networks at the Faculty of Electronics, Wrocław University of Science and Technology. He is actively involved in research and teaching, contributing to teams such as the Machine Learning Team and Advanced Data Analysis Methods Team. His research is supported by projects including IDSTREAM and GEOM, focusing on advanced machine learning techniques for complex data analysis.

Research Interests: His primary research areas include machine learning, deep learning, pattern recognition, classifier ensembles, dynamic classifier selection, data stream mining, handling imbalanced data, and multimodal data analysis. His work emphasizes robust and adaptive models for real-world decision-making tasks, especially under data drift and scarcity conditions.

Publication Trends: His recent publications focus on dynamic ensemble methods for imbalanced data streams, geometric fusion of classifiers, and open-source tools for stream learning. These works reflect a strong trend toward practical, deployable machine learning systems that handle challenging data conditions with high accuracy and adaptability.

Scientific Awards:

• Winner of the Secundus program (2020, 2021, 2022, 2024)
• Appointment to Academia Iuvenum (2024–2026)
• Minister of Education and Science Scholarship for Outstanding Young Scientists (2022)
• Polish Society for Artificial Intelligence Best Doctoral Thesis Award (2021)
• Best Paper Award at ICAISC 2021
• Primus program award (2020–2021)
• Rector's Award for scientific achievements (2019/2020, 2020/2021, 2021/2022)

Advising and Grants: He supervises diploma theses and is involved in significant research projects such as IDSTREAM and GEOM, which support his work in data stream classification and ensemble methods. These projects provide the foundation for his publications and student supervision.

Labs and Teams: He is a key member of the Machine Learning Team and the Advanced Data Analysis Methods Team at Wrocław University of Science and Technology, where he collaborates on developing innovative optimization and classification techniques.