He received the Rössler Prize, ERC Starting Investigator and ERC Consolidator grants, the German Pattern Recognition Award, an NSF CAREER award as well as the ETH Golden Owl teaching award. His research on machine learning and adaptive systems has received awards at several premier conferences and journals, including the ACM SIGKDD Test of Time award 2019 and the ICML Test of Time award 2020. Andreas Krause served as Program Co-Chair for ICML 2018 and General Chair for ICML 2023 and serves as Action Editor for the Journal of Machine Learning Research. In 2023, he was appointed to the United Nations’ High-level Advisory Body on AI.

My research is in machine learning and adaptive systems that actively acquire information, reason and make decisions in large, distributed and uncertain domains, such as sensor networks and the Web. The theoretical aspects include statistical learning (online, active, large-scale, ...), probabilistic reasoning and optimization (in particular submodular and non-convex optimization). My group devises new algorithms, builds models, analyzes large and complex data sets and develops systems that can automatically acquire and reason about highly uncertain information. Our application domains include community sensing, crowdsourcing, computational sustainability, optimal experimental design and information gathering on the web.