Positions held

• Chair of the Department of Systems and Computer Networks
• Former chair of the Scientific Council of Information and Communication Technology (Wroclaw University of Science and Technology) (2021-2024)
• Member of the Scientific Council of the Institute of Computer Science PAS
• Board member of the Committee on Informatics of the Polish Academy of Sciences

Fields of interest

• machine learning and unlearning,
• pattern classification,
• data stream classification, concept drift,
• continual learning (life-long machine learning),
• ensemble learning, classifier ensemble
• inductive learning, data and web mining,
• learning from distributed and streaming data
• imbalanced data classification,

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

New publications

• Radek Svoboda, Sebastián Basterrech, Jędrzej Kozal, Jan Platoš, Michał Woźniak,A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanism - FREE ACCESS, Knowledge-Based Systems, Volume 304 , 25 November 2024, 112482.
• Jędrzej Kozal, Jan Wasilewski, Bartosz Krawczyk, Michał Woźniak, Continual Learning with Weight Interpolation, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024, pp. 4187-4195 BEST PAPER AWARD FOR CLVISION CVPR WORKSHOP 2024
• Guorui Wang, Qian Jiang, Xin Jin, Michał Woźniak, Shaowen Yao, RTM-UAVDet: a real-time multimodal UAV detector, IEEE Transactions on Aerospace and Electronic Systems. 2024.
• Michał Koziarski, Michał Woźniak, Local neighborhood encodings for imbalanced data classification, Machine Laerning, 2024
• Huanyu Guo, Xin Jin, Qian Jiang, Michal Wozniak, Puming Wang, Shaowen Yao, DMF-net: a dual remote sensing image fusion network based on multi-scale convolutional dense connectivity with performance measure, IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-15, 2024, Art no. 5013415, doi: 10.1109/TIM.2024.3370816. +Jędrzej Kozal, Justyna Zwolińska, Marek Klonowski, Michał Woźniak, Defending Network IDS against Adversarial Examples with Continual Learning, 2023 IEEE International Conference on Data Mining Workshops (ICDMW), Shanghai, China, 2023, pp. 60-69, doi: 10.1109/ICDMW60847.2023.00017.
• Jedrzej Kozal, Michał Woźniak, Combining Self-labeling with Selective Sampling, 2023 IEEE International Conference on Data Mining Workshops (ICDMW), Shanghai, China, 2023, pp. 70-79, doi: 10.1109/ICDMW60847.2023.00018.
• Sebastián Basterrech, Andrzej Kasprzak, Jan Platoš, Michał Woźniak, A Continual Learning System with Self Domain Shift Adaptation for Fake News Detection, 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), Thessaloniki, Greece, 2023, pp. 1-10, doi: 10.1109/DSAA60987.2023.10302539.
• 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.