
Tabea Kossen
Researcher · Generative Adversarial Networks
Beuth University of Applied Sciences BerlinAbout
Dr.-Ing. Tabea Kossen is a researcher affiliated with Charité Universitätsmedizin Berlin. She completed her doctorate in machine learning at TU Berlin in cooperation with Charité in 2022, focusing on overcoming scarce medical data and improving anonymization using Generative Adversarial Networks (GANs) for stroke imaging. Her research interests include GANs, deep learning applications in medical imaging, and data anonymization techniques.
Education background: She holds degrees in Cognitive Science from the University of Osnabrück and Computational Neuroscience from TU and Humboldt University Berlin. She actively participates in interdisciplinary research projects funded by organizations such as DFG and BMBF, including APPL-FM, KIP-SDM, and COMFORT, among others.
Her work addresses challenges in medical data scarcity and ethical AI applications in healthcare. Current projects involve advancing AI-driven solutions for clinical imaging analysis and privacy-preserving medical data utilization.
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