Paweł Ksieniewicz

Paweł Ksieniewicz is a Professor at Wrocław University of Science and Technology, affiliated with the Faculty of Electronics and the Department of Computer Systems and Networks. He is a member of the Computer Networks Team and the Machine Learning Team, and serves as a project manager for SWAROG (2021–2025) and contributor to IDSTREAM and GEOM projects.

His research interests include:

• Pattern Recognition
• Data Streams
• Hyperspectral Image Processing
• Imbalanced Data Classification
• Fake News Detection
• Classifier Ensembles

Ksieniewicz's recent publications focus on challenges in data stream mining, particularly in dynamically imbalanced environments, prior probability estimation, and ensemble methods. His work spans applications in cybersecurity (fake news, IoT attack detection) and healthcare (glaucoma diagnosis). He has contributed to open-source tools like the Stream-learn Python library, emphasizing practical and reproducible machine learning research.

His scientific awards include:

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

Ksieniewicz actively supervises students and has collaborated with researchers such as Michał Woźniak, Paweł Zyblewski, and Robert Burduk. He has secured research grants through national projects and serves on the Discipline Council for Technical Computer Science and Teleinformatics. He has also participated in public outreach, including lectures during Science Week and World Information Society Day.

He leads and contributes to multiple research teams, including:

• Machine Learning Team
• Computer Networks Team
• Advanced Data Analysis Methods Team
• Metaheuristics Team