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Aasa Feragen is a Professor at the Technical University of Denmark, specializing in the application of robust interpretable deep learning techniques in medical imaging, particularly fetal development through ultrasound imaging. Feragen has been involved in significant research projects that focus on the intersection of artificial intelligence and healthcare, including uncertainty quantification, algorithmic fairness, and human-AI collaboration. These projects aim to enhance the accuracy and reliability of AI diagnostics in the medical field. Feragen also actively engages in organizing workshops and seminars that promote fairness in AI applications, emphasizing the importance of ethical considerations in technological innovations. With a keen interest in the UN Sustainable Development Goals, Feragen's work significantly contributes to advancing responsible AI methodologies in healthcare settings, which are crucial for fostering sustainable outcomes in public health.
This requirement applies generally across Technical University of Denmark (DTU) MSc programs including Computer Science, Applied Mathematics, and Engineering disciplines. Specific prerequisites vary by department/curriculum.