The Director of the Empirical Inference Department at the Max Planck Institute for Intelligent Systems, one of the world’s leading researchers in the field of machine learning, has been named among the top ten influential minds in the history of German AI.
Tübingen – Bernhard Schölkopf, Director of the Empirical Inference Department at the Max Planck Institute for Intelligent Systems and one of the world’s leading researchers in the field of machine learning, has been named among the top ten influential minds in the history of German AI.
Within the framework of the German Informatic Society’s “#KI50: Artificial Intelligence in Germany – yesterday, today, and tomorrow” project, a jury comprising 18 AI experts has selected “ten influential minds” and “ten important technologies” in the history of German AI. Schölkopf has been honored for his research in the field of machine learning, which shapes the core of research in Cyber Valley, one of Europe’s largest research partnerships.
A co-founder of the core methods in the statistical learning field, Schölkopf’s current research focuses on the development of machine learning methods that recognize causal relationships in large data sets (hence the name empirical inference or conclusion). A machine often finds structures and variable influencing factors in large amounts of data, a feat that the sheer volume of data would make impossible for a human being.
Schölkopf has already received several awards: in 2018, he was awarded the Leibniz Prize in Berlin, the most renowned German research prize. Shortly afterwards, he received the Ste of Baden-Württemberg’s “landesforschungspreis”. He is also a recipient of the J. K. Aggarwal Prize, the Max Planck Research Prize, the Academy Prize of the Academy of Berlin-Brandenburg, the Milner Award of the Royal Society in Great Britain, and the Hector Science Prize.
In 2016, Schölkopf also became a member of the Leopoldina, Germany’s National Academy of Science, and a fellow of the Association for Computing Machinery (ACM) in 2017. He is editor of the Journal of Machine Learning Research, the most important journal in the field of machine learning. He is also one of the founders of the Machine Learning Summer School and has been instrumental in founding and shaping both the Cyber Valley Research Collaboration and the ELLIS Initiative (European Laboratory for Learning and Intelligent Systems).
(Release by: Empirical Inference Department at the Max Planck Institute for Intelligent Systems)