Machine Learning

In complex interacting systems, such as renewable energy systems, where parts of the system depend on the weather, climate, and human behaviour, forecasting is challenging and uncertainty plays a significant role. In this research area, we focus on adapting and developing forecasting methods that can be used reliably in complex systems while giving valid and useful estimates about the uncertainty.

Main Research Interests:

• Calibrated uncertainty estimates in regression and forecasting
• Probabilistic forecasting

Recent Research Highlight