Img 2694 small
prof. dr hab. inż.

Michał Woźniak


Kierownik katedry

Zespół Uczenia Maszynowego

Zainteresowania badawcze
Machine Learning
Pattern Recognition
Classifier Ensemble
Data Stream Mining

Prowadzi w tym semestrze
Seminarium dyplomowe

info Consultation hours: Wednesday 9a.m.-11p.m. (please email me earlier)

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
  1. Katarzyna Stąpor, Paweł Ksieniewicz, Salvador Garcia, Michał Woźniak, How to design the fair experimental classifier evaluation Applied Soft Computing, Volume 104, June 2021, 107219 FREE ACCESS BY April,27.
  2. Joanna Grzyb, Jakub Klikowski, Hellinger Distance Weighted Ensemble for Imbalanced Data Stream Classification, Journal of Computational Science, Volume 51, April 2021, 101314 (free access by April 03, 2021) arxiv
  3. 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
  4. 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.
  5. Bartosz Krawczyk, Michał Koziarski, Michał Woźniak, Radial-Based Oversampling for Multi-Class Imbalanced Data Classification, IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 8, pp. 2818-2831, Aug. 2020, doi: 10.1109/TNNLS.2019.2913673.
  6. Michał Koziarski, Michał Woźniak, Bartosz Krawczyk, Combined cleaning and resampling algorithm for multi-class imbalanced data with label noise, Knowledge-Based Systems, Volume 204, 27 September 2020, 106223.
  7. Amgad M. Mohammed, Enrique Onieva, Michał Wozniak, Training set selection and swarm intelligence for enhanced integration inmultiple classifier systems, Applied Soft Computing, Volume 95, October 2020, 106568.
MSc thesis topics
  1. Fake news detection.
  2. Video/image manipulation discovery.
  3. Explainable AI/ML.
  4. Data stream classification.
  5. Learning from Imabalanced data.

today
Rozkład zajęć
  • Środa
  • Seminarium dyplomowe C-4: 33 | 13.15—15.00
  • Seminarium dyplomowe C-4: 33 | 15.15—16.55

bookmark
Wybrane publikacje

menu