Natural and Life Sciences
Nicole Ludwig just started an Early Career Research Group at the "Machine Learning for Science-Cluster for Excellence" at the University of Tübingen. She develops new machine learning algorithms that enable and support a sustainable energy system of the future. A special focus is on the role of uncertainties, which play an increasingly important role in energy systems with a high share of renewable energy resources, e.g. due to weather and climate. Her research, therefore, focuses primarily on probabilistic machine learning to understand and quantify uncertainty in sustainable energy systems. For her work, Nicole Ludwig has received several Best Paper Awards from international conferences in the field of energy informatics, as well as the KIT Doctoral Award for her PhD thesis. Nicole studied in Freiburg and Oslo and did her PhD in Karlsruhe and Oxford. She has the potential to become one of the leading experts in the intersection of ML and sustainable energy systems.
How can we use machine learning to create and support a sustainable energy system of the future, that ideally relies on as many renewable energy resources as possible while being as robust and reliable as we wish to have it. As renewable energy resources depend on the weather and climate, which are both highly stochastic and uncertain, I am focusing on probabilistic machine learning and mostly working with time series data.