• Chair of the Department of Systems and Computer Networks
• Chair of the Scientific Council of Information and Communication Technology (Wroclaw University of Science and Technology)
• Member of the Scientific Council of the Institute of Computer Science PAS
• Member of the Committee on Informatics of the Polish Academy of Sciences

Fields of interest

• machine learning,
• data stream mining,
• data stream classification, concept drift,
• ensemble learning, classifier ensemble
• inductive learning, data and web mining,
• learning on distributed and streaming data
• pattern classification,
• imabalanced data classification,
• pattern recognition with context
• telemedicine and medical decision support

Google Scholar profile
ORCID
ResearchGate profile
ResearchID profile
List of publication in DONA database - maintained by my University

New publications

• Jakub Klikowski, Michał Woźniak, Deterministic Sampling Classifier with weighted Bagging for drifted imbalanced data stream classification, Applied Soft Computing, 2022. FREEE ACCESS by June 12, 2022
• Jędrzej Kozal, Filip Guzy, Michał Woźniak, Employing chunk size adaptation to overcome concept drift, Journal of Universal Computer Science, 28(3): 249-268, 2022.
• Weronika Węgier, Michał Koziarski, Michał Woźniak, Multicriteria classifier ensemble learning for imbalanced data, IEEE ACCESS
• Amgad M. Mohammed, Enrique Onieva, Michał Woźniak, Gonzalo Martinez-Munoz, An Analysis of Heuristic Metrics For Classifier Ensemble Pruning Based on Ordered Aggregation, Pattern Recognition, Volume 124, April 2022, 108493.
• Filip Guzy, Michał Woźniak, Bartosz Krawczyk, Evaluating and Explaining Generative Adversarial Networks for Continual Learning under Concept Drift, ICDM 2021, Workshop on Continual Learning and Adaptation for Time Evolving Data
• Amgad M. Mohammed, Enrique Onieva, Michał Woźniak, Selective Ensemble of Classifiers Trained on Selective Samples, Neurocomputing.
• Michał Koziarski, Colin Bellinger, Michał Woźniak, RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification, Machine Learning 110, pages 3059–3093 (2021).
• Michał Choraś, Michał Woźniak, The double-edged sword of AI: Ethical Adversarial Attacks to counter artificial intelligence for crime, AI and Ethics accepted

• Katarzyna Stąpor, Paweł Ksieniewicz, Salvador Garcia, Michał Woźniak, How to design the fair experimental classifier evaluation Applied Soft Computing, Volume 104, June 2021, 107219 .

• Joanna Grzyb, Jakub Klikowski, Hellinger Distance Weighted Ensemble for Imbalanced Data Stream Classification, Journal of Computational Science, Volume 51, April 2021, 101314 arxiv

• Michał Choraś, Konstantinos Demestichas, Agata Giełczyk, Álvaro Herrero, Paweł Ksieniewicz, Konstantina Remoundou, Daniel Urda, Michał Woźniak, Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study, Applied Soft Computing, Volume 101, March 2021, 107050. arxiv

• Paweł Zyblewski, Robert Sambourin, Michał Woźniak, Preprocessed dynamic classifier ensemble selection for highly imbalanced drifted data streams, Information Fusion, Volume 66, February 2021, Pages 138-154.

MSc thesis topics

1. Fake news detection.
2. Video/image manipulation discovery.
3. Explainable AI/ML.
4. Data stream classification.
5. Learning from imbalanced data.