Education within Multimodal Reasoning for Robotics and Process Intelligence

Our research group is strongly involved in education, contributing to both bachelor’s and master’s programs through teaching, supervision, and project guidance. 

At the Bachelor of Energy and Applied Industrial Electronics, we teach courses that cover the foundations of programming, modeling, and control, as well as advanced topics in real-time systems, robotics, artificial intelligence, and cyber-physical systems. These courses are designed to equip students with both theoretical understanding and hands-on skills essential for engineering practice.

At the master’s level, we supervise and teach in the MSc in Advanced Power Electronics and the MSc in Offshore Energy Systems. Our teaching emphasizes system identification, optimization, dynamic modeling of machines, and process control and surveillance. In the Advanced Power Electronics specialization, we focus on advanced topics such as condition monitoring, reliability, adaptive and predictive control, artificial intelligence, and fault-tolerant systems. Across all levels, our teaching connects cutting-edge research with practical applications, preparing students to address complex challenges in robotics, energy systems, and industrial processes.

 

Ongoing projects

• OPTIMIZE: Optimizing Microbial Fermentation with Deep Reinforcement Learning: Advancing Control in Complex Biochemical Systems
• AITEKS: Artificial Intelligence Tech Support
• ROPE: Building the foundation for the use of fiber rope in cranes for tall wind turbines

 

Completed projects

• Deep Leaning Model Predictive Control for Reduction of N2O Emissions from WWTPs
• RecaP: Capture, recycling and societal management of phosphorus in the environment
• Internal blade inspection system
• Deep Learning in Robotics and Big Data for Applications in Wind-turbine Inspections
• Smart‐Spider: Autonomous self‐driven robot for cost‐effective in‐line inspection of subsea pipeline integrity