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Roland Löwe is an Associate Professor at the Technical University of Denmark, leading the Water Systems section. His work focuses on integrating machine learning into water applications, with a strong emphasis on flood risk assessment and the efficiency of water infrastructure planning. He has directed research projects emphasizing urban water management and has collaborated with municipalities to apply scientific machine learning in practical contexts. His academic journey includes a PhD in Probabilistic Forecasting and extensive experience in hydrology, equipping him to address complex environmental challenges. Löwe’s contributions also extend to the United Nations Sustainable Development Goals, particularly in areas related to sustainable urban development and adaptive water management strategies.
Technical University of Denmark • Lyngby, Denmark
Conducting advanced research in hydrology and water systems.
Krüger A/S • Denmark
Worked on design and implementation of water management projects.
Institute of Technical Scientific Hydrology (itwh) • Germany
Engaged in research and analysis of hydrological systems.
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.