Adaptive control and decision-making in energy systems

Research:

• Machine learning for decision making in energy systems
• Safe reinforcement learning for energy systems
• Self-learning algorithms for energy optimization and load management
• Synthetic energy data generation with generative adversarial networks

Note for interested students:

Students who would like to work on one of these topics as part of a Master's thesis are welcome to send an e-mail to goekhan.demirel@kit.edu. The topics can be individually adapted to the respective prior knowledge and interests.