Franz Baumdicker's research focuses on mathematical models for the evolution of microbes. His group investigates how machine learning can leverage phylogenetic information in population genetics.
Christian Baumgartner's research is at the interface of machine learning and automated medical image analysis with the goal to create safe and robust clinical prediction systems.
Konstantin Genin is interested in learning-theoretic approaches to issues in the ethics and methodology of statistics and machine learning.
Bedartha Goswami's research aims to investigate climate processes and unravel the complexity of climatic systems with tools and techniques from the wide domain of machine learning.
Charley Wu’s research studies the specific shortcuts and cognitive algorithms that people use to make inference tractable. His work seeks to narrow the gap between human and machine learning.
Early Career Research Groups established by the Cluster
Nicole Ludwig's research focuses on probabilistic machine learning seeking to understand the role of uncertainty in future sustainable energy systems.