Manuel Dahmen

Dr. Manuel Dahmen serves as Head of Department at the Institute of Climate and Energy Systems (ICE-1) within the Research Center Jülich. His research focuses on designing sustainable and cost-efficient energy systems through numerical optimization and deep learning techniques. He leads efforts in advancing energy system technology, particularly in optimizing renewable energy integration, process network analysis, and the co-design of fuels and engines.

His work emphasizes innovative applications of machine learning, such as physics-informed neural networks and reinforcement learning, to address challenges in energy system design and operation. Key areas include reducing greenhouse gas emissions in industrial processes, optimizing energy networks, and developing data-driven models for dynamic process control.

Dr. Dahmen’s contributions span algorithm development (e.g., MUSE-BB decomposition algorithms), energy system scenario generation, and robust design methodologies under uncertainty. His research bridges computational methods with practical energy solutions, aiming to achieve decarbonization in industries like copper production and transportation.

Publications highlight advancements in renewable energy integration, fuel design for spark-ignition engines, and the application of graph neural networks for molecular property prediction. His interdisciplinary approach fosters collaboration across chemical engineering, computer science, and energy economics to tackle global sustainability challenges.