Positions held

• 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,
• imbalanced 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

• Weronika Węgier, Michał M. Koziarski, Michał Woźniak, Optimized hybrid imbalanced data sampling for decision tree training. Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion, July 15-19, 2023, Lisbon, Portugal, pp. 339-342.
• Jędrzej Kozal, Michał Woźniak, Increasing depth of neural networks for life-long learning, Information Fusion, Volume 98, October 2023, 101829
• Michał Woźniak, Paweł Zyblewski, Paweł Ksieniewicz, Active Weighted Aging Ensemble for Drifted Data Stream Classification arxiv version, Information Sciences, Volume 630, June 2023, Pages 286-304.
• Michał Panek, Adam Pomykała, Ireneusz Jabłoński, Michał Woźniak, 5G/5G+ network management employing AI-based continuous deployment, Applied Soft Computing, 109984, 2023.
• Paweł Ksieniewicz, Paweł Zyblewski, Weronika Borek-Marciniec, Rafał Kozik, Michał Choraś, Michał Woźniak, Alphabet Flatting as a variant of n-gram feature extraction method in ensemble classification of fake news, Engineering Applications of Artificial Intelligence, Volume 120, April 2023, 105882.
• Joanna Grzyb, Michał Woźniak, SVM ensemble training for imbalanced data classification using multi-objective optimization techniques, Applied Intelligence
• Sebastián Basterrech, Michał Woźniak, Tracking changes using Kullback-Leibler divergence for the continual learning, 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Prague, Czech Republic, 2022, pp. 3279-3285. arxiv
• Jakub Klikowski, Michał Woźniak, Deterministic Sampling Classifier with weighted Bagging for drifted imbalanced data stream classification, Applied Soft Computing, 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, vol. 10, pp. 16807-16818, 2022.
• 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, 108493, 2022.
• Amgad M. Mohammed, Enrique Onieva, Michał Woźniak, Selective Ensemble of Classifiers Trained on Selective Samples, Neurocomputing, vol.482, pp. 197-211, 2022.

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.