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Stephan Günnemann conducts research in the field of machine learning and data analytics. His main research focuses on making machine learning techniques reliable, enabling safe and robust use in various application domains. Günnemann is particularly interested in studying machine learning methods targeting complex data domains, specifically in graphs/networks and temporal data. He acquired his doctoral degree in 2012 from RWTH Aachen University in the field of computer science. From 2012 to 2015, he served as an associate at Carnegie Mellon University in the USA, initially as a postdoctoral fellow before becoming a senior researcher. He has also been a visiting researcher at Simon Fraser University in Canada and a research scientist at the Research & Technology Center of Siemens AG. In 2015, he established the Emmy Noether research group at the Technical University of Munich, where he became a professor in 2016. He is the Executive Director of the Munich Data Science Institute and Director of the Konrad Zuse School of Excellence in Reliable AI.
Technical University of Munich • Munich, Germany
Established the Emmy Noether research group and currently leads research in machine learning and data analytics.