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Teresa Rebelo is a PhD student whose research focuses on the intersection of machine learning and public health, particularly in assessing healthy lifestyles. Her recent project involves using machine learning assessments to analyze dietary risks and their implications on health outcomes. Teresa actively participates in several research projects aimed at promoting sustainable healthy living and contributes to discussions at numerous health conferences around the world. Her work aligns with the United Nations Sustainable Development Goals, which aim to eradicate poverty and protect the planet. She has been recognized for her contributions, receiving several awards such as the Otto Mønsted’s Foundation Travel Grant and the Session Presentation Award from the International Society for Environmental Epidemiology.
Technical University of Denmark • Kgs. Lyngby, Denmark
Conducting research on machine learning applications in public health, specifically assessing dietary risks.
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.