
About
Natalia Kowalczyk serves as an Assistant Lecturer at the Department of Biomedical Engineering within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. Her academic profile demonstrates a strong focus on applying advanced computational techniques to solve critical healthcare challenges, particularly in maternal health monitoring and biomedical signal processing.
Her research interests span multiple interdisciplinary domains including biomedical engineering, machine learning applications in healthcare, digital twin technology for medical diagnostics, and federated learning systems for privacy-preserving healthcare AI. Kowalczyk's work particularly emphasizes maternal health monitoring systems, respiratory signal analysis, and the application of synthetic data in medical diagnostics.
Analysis of her recent publications reveals a consistent trajectory toward developing AI-driven healthcare solutions with practical clinical applications. Her research demonstrates expertise in machine learning algorithm development, particularly XGBoost and federated learning approaches, applied to obstetric healthcare challenges including preeclampsia prediction and gestational diabetes diagnosis. She also contributes to computer vision applications in biomedical contexts and edge computing for healthcare infrastructure.
Natalia Kowalczyk collaborates extensively with researchers including J. Rumiński, M. Mazur-Milecka, and T. Kocejko across multiple healthcare technology projects. Her work bridges theoretical machine learning advancements with practical healthcare implementations, particularly in maternal health monitoring and pandemic response systems.
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