Independent Research Groups established by the Cluster
Franz Baumdicker
Mathematical and Computational Population Genetics
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
Machine Learning in Medical Image Analysis
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
Epistemology and Ethics of Machine Learning
Konstantin Genin is interested in learning-theoretic approaches to issues in the ethics and methodology of statistics and machine learning.
Bedartha Goswami
Machine Learning in Climate Science
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.
Nicole Ludwig
Machine Learning in Sustainable Energy Systems
Nicole Ludwig's research focuses on probabilistic machine learning seeking to understand the role of uncertainty in future sustainable energy systems.
Claire Vernade
Lifelong Reinforcement Learning
The Lifelong Reinforcement Learning Lab studies interactive machine learning problems where feedback loops and long-term impact of actions must be taken into account to train agents. In particular, we want to build agents who anticipate changes in the environment and show adaptive and sample-efficient behaviours that improve with experience.
Charley Wu
Human and Machine Cognition Lab
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
Katharina Eggensperger
Automated machine learning for Science
Katharina Eggensperger researches how to make machine learning easily accessible and more efficient through automated machine learning (AutoML) to advance and augment scientific research.