Michal Kruczkowski

PhD in Computer Science, Bydgoszcz University of Science and Technology, Bydgoszcz Poland, Hanyang University, Seoul, South Korea

Research Expertise

AI
machine learning
data mining
healthcare
medicine 4.0
Biomedical Engineering
Optics and Photonics
Smart Sensors

About

Michal Kruczkowski is an accomplished professional with extensive experience in the implementation of AI algorithms in accordance with the fourth industrial revolution. With a strong background in business and academia, he has successfully led numerous projects related to digital transformation and education. His expertise is primarily focused on safety systems and predictive modelling in healthcare, and he currently leads a multidisciplinary data science research group that conducts cutting-edge research on applied artificial intelligence and predictive modelling. In addition, Michal is a dedicated educator who has introduced over 100 students each year to the most relevant techniques and applications of AI and predictive modelling. Follow Michal for insights into the latest developments in AI and predictive modelling, as well as updates on his ongoing research and educational initiatives.

Publications

Support Vector Machine for Malware Analysis and Classification

2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) / Aug 01, 2014

Kruczkowski, M., & Szynkiewicz, E. N. (2014, August). Support Vector Machine for Malware Analysis and Classification. 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). https://doi.org/10.1109/wi-iat.2014.127

Cross-layer analysis of malware datasets for malicious campaigns identification

2015 International Conference on Military Communications and Information Systems (ICMCIS) / May 01, 2015

Kruczkowski, M., Niewiadomska-Szynkiewicz, E., & Kozakiewicz, A. (2015, May). Cross-layer analysis of malware datasets for malicious campaigns identification. 2015 International Conference on Military Communications and Information Systems (ICMCIS). https://doi.org/10.1109/icmcis.2015.7158682

Predictions of cervical cancer identification by photonic method combined with machine learning

Scientific Reports / Mar 08, 2022

Kruczkowski, M., Drabik-Kruczkowska, A., Marciniak, A., Tarczewska, M., Kosowska, M., & Szczerska, M. (2022). Predictions of cervical cancer identification by photonic method combined with machine learning. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-07723-1

FP-tree and SVM for Malicious Web Campaign Detection

Intelligent Information and Database Systems / Jan 01, 2015

Kruczkowski, M., Niewiadomska-Szynkiewicz, E., & Kozakiewicz, A. (2015). FP-tree and SVM for Malicious Web Campaign Detection. In Lecture Notes in Computer Science (pp. 193–201). Springer International Publishing. https://doi.org/10.1007/978-3-319-15705-4_19

Estimation of light detection efficiency for different light guides used in time-resolved near-infrared spectroscopy

Biocybernetics and Biomedical Engineering / Jan 01, 2015

Milej, D., Kruczkowski, M., Kacprzak, M., Sawosz, P., Maniewski, R., & Liebert, A. (2015). Estimation of light detection efficiency for different light guides used in time-resolved near-infrared spectroscopy. Biocybernetics and Biomedical Engineering, 35(4), 227–231. https://doi.org/10.1016/j.bbe.2015.05.003

Low-Coherence Fibre-Optic Interferometric Sensors

Acta Physica Polonica A / Oct 01, 2011

Jedrzejewska-Szczerska, M., Gnyba, M., & Kosmowski, B. B. (2011). Low-Coherence Fibre-Optic Interferometric Sensors. Acta Physica Polonica A, 120(4), 621–624. https://doi.org/10.12693/aphyspola.120.621

Machine learning for predictions of cervical cancer identification – preliminary investigation based on refractive index

Oct 01, 2021

Kruczkowski, M., Drabik-Kruczkowska, A., Marciniak, A., Tarczewska, M., Kosowska, M., & Szczerska, M. (2021). Machine learning for predictions of cervical cancer identification – preliminary investigation based on refractive index. https://doi.org/10.21203/rs.3.rs-948525/v1

An algorithm for assessment of inflow and washout of optical contrast agent to the brain by analysis of time-resolved diffuse reflectance and fluorescence signals

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) / Jul 01, 2013

Milej, D., Kruczkowski, M., Gerega, A., Sawosz, P., Maniewski, R., & Liebert, A. (2013, July). An algorithm for assessment of inflow and washout of optical contrast agent to the brain by analysis of time-resolved diffuse reflectance and fluorescence signals. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). https://doi.org/10.1109/embc.2013.6609901

Implementation of SiN thin film in fiber-optic sensor working in telecommunication range of wavelengths

Scientific Reports / Nov 17, 2021

Pawłowska, S., Gierowski, J., Stonio, B., Juchniewicz, M., Ficek, M., Kruczkowski, M., & Szczerska, M. (2021). Implementation of SiN thin film in fiber-optic sensor working in telecommunication range of wavelengths. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-00195-9

The Rough Set Analysis for Malicious Web Campaigns Identification

Image Processing and Communications Challenges 10 / Nov 01, 2018

Kruczkowski, M., & Miciak, M. (2018). The Rough Set Analysis for Malicious Web Campaigns Identification. In Advances in Intelligent Systems and Computing (pp. 208–215). Springer International Publishing. https://doi.org/10.1007/978-3-030-03658-4_25

SYSTEM DO WYKRYWANIA KAMPANII ZŁOŚLIWEGO OPROGRAMOWANIA

PRZEGLĄD TELEKOMUNIKACYJNY - WIADOMOŚCI TELEKOMUNIKACYJNE / Sep 05, 2015

Kruczkowski, M. (2015). SYSTEM DO WYKRYWANIA KAMPANII ZŁOŚLIWEGO OPROGRAMOWANIA. PRZEGLĄD TELEKOMUNIKACYJNY - WIADOMOŚCI TELEKOMUNIKACYJNE, 1(8–9), 117–125. https://doi.org/10.15199/59.2015.8-9.16

Links & Social Media

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