prof. dr hab. inż. Marcin Woźniak
Stanowisko: profesorPełniona funkcja: Dziekan; Zastępca Kierownika Katedry
Pokój do pracy i konsultacji: MS 517
Telefon służbowy: 32 237 13 41
Email: Marcin.Wozniak@polsl.pl
Numer ORCID: 0000-0002-9073-5347
Plan zajęć: https://plan.polsl.pl/
Zespół dydaktyczny: Wydział Matematyki Stosowanej, kierunek Informatyka
Dyplom magistra: Politechnika Śląska, 2007
Stopień doktora: Politechnika Śląska
Stopień doktora habilitowanego: Politechnika Częstochowska, 2019
Tytuł profesora: 21 grudnia 2022
Zainteresowania naukowe: modelowanie systemów, sztuczna inteligencja, sieci neuronowe, wnioskowanie rozmyte, algorytmy pozyskiwanie wiedzy
Najważniejsze prace naukowe:
1. M. Woźniak, J. Szczotka, A. Sikora, A. Zielonka : Fuzzy logic type-2 intelligent moisture control system. Expert Systems with Applications, Vol. 238 Part A, DOI: 10.1016/j.eswa.2023.121581, ISSN 1873-6793, Elsevier 2024, p. 121581.
2. W. Feng, J. Zhang, Y. Chen, Z. Qin, Y. Zhang, M. Ahmad, M. Woźniak : Exploiting robust quadratic polynomial hyperchaotic map and pixel fusion strategy for efficient image encryption. Expert Systems with Applications, Vol. 246, Part XX, DOI: 10.1016/j.eswa.2024.123190, ISSN 1873-6793, Elsevier 2024, p. 123190.
3. W. Wei, Q. Ke, D. Połap, M. Woźniak : Spline interpolation and deep neural networks as feature extractors for signature verification purposes. IEEE Internet of Things Journal, Vol. 10, No. 3, DOI: 10.1109/JIOT.2021.3086034, ISSN 2327-4662, IEEE, USA 2023, pp. 2152-2161.
4. W. Wei, Q. Ke, M. Pleszczyński, A. Zielonka, M. Woźniak : Vehicle Parking Navigation Based on Edge Computing with Diffusion Model and Information Potential Field. IEEE Transactions on Services Computing, Vol. 16, No. 5, DOI: 10.1109/TSC.2023.3286332, ISSN 1939-1374, IEEE, USA 2023, pp. 3827 - 3836.
5. M. Woźniak, M. Wieczorek, J. Siłka : BiLSTM deep neural network model for imbalanced medical data of IoT systems. Future Generation Computer Systems, Vol. 141, DOI: 10.1016/j.future.2022.12.004, ISSN 0167-739X, Elsevier 2023, p. 489-499.
6. M. Woźniak, A. Sikora, A. Zielonka, K. Kaur, M. Shamim Hossain, M. Shorfuzzaman : Heuristic optimization of multi-pulse rectifier for reduced energy consumption. IEEE Transactions on Industrial Informatics, Vol. 18, No. 8, DOI: 10.1109/TII.2021.3117976, ISSN 1941-0050, IEEE, USA 2022, pp. 5515-5526.
7. W. Dong, J. Wu, X. Zhang, Z. Bai, P. Wang, M. Woźniak : Improving Performance and Efficiency of Graph Neural Networks by Injective Aggregation. Knowledge-Based Systems, Vol. 254, DOI: 10.1016/j.knosys.2022.109616, ISSN 0950-7051, Elsevier 2022, p. 109616.
8. Q. Ke, J. Siłka, M. Wieczorek, Z. Bai, M. Woźniak : Deep neural network heuristic hierarchization for cooperative intelligent transportation fleet management, IEEE Transactions on Intelligent Transportation Systems, Vol. 23, No. 9, DOI: 10.1109/TITS.2022.3195605, ISSN 1558-0016, IEEE, USA 2022, pp. 16752-16762.
9. M. Woźniak, A. Zielonka, A. Sikora : Driving support by type-2 fuzzy logic control model. Expert Systems with Applications Vol. 207, DOI: 10.1016/j.eswa.2022.117798, ISSN 1873-6793, Elsevier 2022, p. 117798.
10. M. Woźniak, J. Siłka, M. Wieczorek, M. Alrashoud : Recurrent Neural Network model for IoT and networking malware threads detection. IEEE Transactions on Industrial Informatics, Vol. 17, No. 8, DOI: 10.1109/TII.2020.3021689, ISSN 1941-0050, IEEE, USA 2021, pp. 5583-5594.
11. M. Woźniak, M. Wieczorek, J. Siłka, D. Połap : Body Pose Prediction Based on Motion Sensor Data and Recurrent Neural Network. IEEE Transactions on Industrial Informatics, Vol. 17, No. 3, DOI: 10.1109/TII.2020.3015934, ISSN 1941-0050, IEEE, USA 2021, pp. 2101 - 2111.
12. M. Woźniak, A. Zielonka, A. Sikora, Md. Jalil Piran, A. Alamri : 6G-Enabled IoT Home Environment Control Using Fuzzy Rules. IEEE Internet of Things Journal, Vol. 8, No. 7, DOI: 10.1109/JIOT.2020.3044940, ISSN 2327-4662, IEEE, USA 2021, pp. 5442-5452.
13. D. Połap, M. Woźniak : A hybridization of distributed policy and heuristic augmentation for improving federated learning approach. Neural Networks, Vol. 146, DOI: 10.1016/j.neunet.2021.11.018, ISSN 0893-6080, Elsevier 2021, pp. 130-140.
14. D. Połap, M. Woźniak : Meta-heuristic as manager in federated learning approaches for image processing purposes. Applied Soft Computing, Vol. 113, Part A, DOI: 10.1016/j.asoc.2021.107872, ISSN 1568-4946, Elsevier 2021, p. 107872.
15. W. Dong, J. Wu, Z. Bai, Y. Hu, W. Li, W. Qiao, M. Woźniak : MobileGCN applied to low-dimensional node feature learning. Pattern Recognition, Vol. 112, DOI: 10.1016/j.patcog.2020.107788, ISSN 0031-3203, Elsevier 2021, p. 107788.
16. D. Połap, M. Woźniak : Red fox optimization algorithm. Expert Systems with Applications, Vol. 166, DOI: 10.1016/j.eswa.2020.114107, ISSN 1873-6793, Elsevier 2021, p. 114107.
17. G. Capizzi, G. Lo Sciuto, C. Napoli, D. Połap, M. Woźniak : Small lung nodules detection based on fuzzy-logic and probabilistic neural network with bio-inspired reinforcement learning. IEEE Transactions on Fuzzy Systems, Vol. 28, No. 6, DOI: 10.1109/TFUZZ.2019.2952831, ISSN 1063-6706, IEEE, USA 2020, pp. 2651-2658.
18. M. Woźniak, D. Połap : Intelligent home systems for ubiquitous user support by using neural networks and rule-based approach. IEEE Transactions on Industrial Informatics, Vol. 16, No. 4, DOI: 10.1109/TII.2019.2951089, ISSN 1941-0050, IEEE, USA 2020, pp. 1178-1189.
19. G. Capizzi, G. Lo Sciuto, C. Napoli, G. Susi, M. Woźniak : A spiking neural network-based long-term prediction system for biogas production. Neural Networks, Vol. 129, DOI: 10.1016/j.neunet.2020.06.001, ISSN: 1879-2782, Elsevier 2020, pp. 271-279.
20. D. Połap, K. Kęsik, A. Winnicka, M. Woźniak : Strengthening the perception of the virtual worlds in a virtual reality environment. ISA Transactions, Vol. 102, DOI: 10.1016/j.isatra.2020.02.023, ISSN: 0019-0578, Elsevier 2020, pp. 397-406.
21. W. Wei, B. Zhou, D. Połap, M. Woźniak : A regional adaptive variational PDE model for computed tomography image reconstruction. Pattern Recognition, Vol. 92C, DOI: 10.1016/j.patcog.2019.03.009, ISSN 0031-3203, Elsevier 2019, pp. 64-81.
22. A. Lauraitis, R. Maskeliūnas, R. Damaševičius, D. Połap, M. Woźniak : A smartphone application for automated decision support in cognitive task based evaluation of central nervous system motor disorders. IEEE Journal of Biomedical and Health Informatics, Vol. 23, No. 5, DOI: 10.1109/JBHI.2019.2891729, ISSN 2168-2194, IEEE, USA 2019, pp. 1865 - 1876.
23. M. Woźniak, D. Połap : Bio-Inspired Methods modeled for respiratory disease detection from medical images. Swarm and Evolutionary Computation, Vol. 41, DOI: 10.1016/j.swevo.2018.01.008, ISSN: 2210-6502, Elsevier 2018, pp. 69-96.
24. M. Woźniak, K. Książek, J. Marciniec, D. Połap : Heat production optimization using bio-inspired algorithms. Engineering Applications of Artificial Intelligence, Vol. 76, DOI: 10.1016/j.engappai.2018.09.003, ISSN 0952-1976, Elsevier 2019, pp. 185-201.
25. M. Woźniak, D. Połap, L. Kośmider, T. Cłapa : Automated fluorescence microscopy image analysis of Pseudomonas aeruginosa bacteria in alive and dead stadium. Engineering Applications of Artificial Intelligence, Vol. 67, DOI: 10.1016/j.engappai.2017.09.003, ISSN 0952-1976, Elsevier 2018, pp. 100-110.
26. F. Beritelli, G. Capizzi, G. Lo Sciuto, C. Napoli, M. Woźniak : A novel training method to preserve generalization of RBPNN classifiers applied to ECG signals diagnosis. Neural Networks, Vol. 108, DOI: 10.1016/j.neunet.2018.08.023, ISSN: 0893-6080, Elsevier 2018, pp. 331-338.
27. M. Woźniak, D. Połap : Adaptive neuro-heuristic hybrid model for fruit peel defects detection. Neural Networks, Vol. 98, DOI: 10.1016/j.neunet.2017.10.009, ISSN: 0893-6080, Elsevier 2018, pp. 16-33.
28. M. Woźniak, D. Połap : Object detection and recognition via clustered features. Neurocomputing, Vol. 320, DOI: 10.1016/j.neucom.2018.09.003, ISSN 0925-2312, Elsevier 2018, pp. 76-84.
29. M. Woźniak, D. Połap : Hybrid neuro-heuristic methodology for simulation and control of dynamic systems over time interval. Neural Networks, Vol. 93, DOI: 10.1016/j.neunet.2017.04.013, ISSN: 0893-6080, Elsevier 2017, pp. 45-56.
