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Søren Juhl Andersen is an Associate Professor at the Technical University of Denmark, focusing on machine learning applications in wind energy, specifically wind farm wake aerodynamics. His research interests involve practices that contribute to the United Nations Sustainable Development Goals, particularly related to energy efficiency and environmental sustainability in wind energy systems. He leads and supervises PhD students on projects that utilize artificial intelligence to enhance wind power generation through better dynamic modeling and simulation of turbulence dynamics. Andersen has extensive experience in interdisciplinary research collaborations across Europe and Asia, contributing to significant advancements in the understanding of wake dynamics and energy entrainment in wind turbines. As a guest lecturer, he actively shares his expertise in multi-rotor performance and control strategies in various conferences, promoting innovative approaches to renewable energy challenges.
Technical University of Denmark • Kgs. Lyngby, Denmark
Conducted research and taught courses related to wind energy technologies and machine learning applications.
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.