Explainable AI for Energy Applications

This PhD, will explore and develop Explainable AI (XAI) for energy systems. These methods will be able to provide insights into how the 'black-box' methods are functioning, approaching glass-box methods. Methods explored include but are not limited to; deep learning, ensemble learning and causal inference. The research contribution will cover a wide spectrum building theoretical foundations in this rapidly developing field while also contributing to real world applications such as wind turbine failure. The research will be conducted in collaboration with the EDF digital innovation team.