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Alan Wai Hou LioView profile

Associate Professor

• Wind Turbine Control
• Predictive Modeling
• Renewable Energy Systems
• +2 more

Alan Wai Hou Lio is an Associate Professor at the Technical University of Denmark's Department of Wind and Energy Systems, specializing in wind turbine control and energy system dynamics. His research develops advanced control strategies to optimize energy capture and reduce structural loads in wind farms. Research Focus: Predictive wind turbine control algorithms LiDAR-assisted flow measurement techniques Offshore floating turbine dynamics Real-time estimation methods for turbulent flows His publications demonstrate consistent focus on experimental validation of control theories, with recent work emphasizing field implementation challenges. Current projects include DigiWind (digital wind energy systems) and PowerKey (wind plant optimization). Education: PhD in Automatic Control (Sheffield, 2017), M.Eng in Electrical Engineering (Imperial College London, 2012).

Jakob Kjøbsted HuusomView profile

Professor

• Process Control
• Model Predictive Control (MPC)
• Optimization
• +7 more

Jakob Kjøbsted Huusom is a Professor at the Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU). His research emphasizes advanced process control, model development for the process industry, and sustainable technologies. He is affiliated with the KT Consortium PROSYS and the Process and Systems Engineering Centre (PROSYS), contributing to UN Sustainable Development Goals related to affordable energy and climate action. His work spans hybrid modeling approaches integrating AI with first-principles methods, optimization of industrial processes, and real-time adaptive systems. Current projects include MPC tuning algorithms, enzymatic biodiesel production control, energy-efficient distillation technologies, and electrification of industrial processes using renewable energy. As a supervisor, he guides multiple PhD students in topics such as risk monitoring, model-based digitalization, and Power-to-X applications. His research tools and methodologies address challenges in process identification, state estimation, and controller design, with a focus on scalability and real-world implementation. Collaborations include international teams in Julia-based simulation tools and hybrid neural network modeling. His contributions advance both theoretical frameworks and practical solutions for sustainable industrial systems.