Bernhard Schölkopf
Conference 2026
Panel: Building Europe’s AI-Powered Innovation Economy
Bernhard Schölkopf studies machine learning and causal inference, with fundamental contributions to kernel methods, causality, and representation learning, applied to fields ranging from astronomy to robotics. Trained in physics and mathematics, he earned a Ph.D. in computer science in 1997 and joined the Max Planck Society in 2001. He is Scientific Director of the ELLIS Institute Tübingen and the Max Planck Institute for Intelligent Systems, and an affiliated professor at ETH Zurich.
His work has been recognized by international awards, including the ACM-AAAI Allen Newell Award, the BBVA Foundation Frontiers of Knowledge Award, the Gottfried Wilhelm Leibniz Prize, and the Royal Society Milner Award. He co-founded the ELLIS Society and helped establish the Journal of Machine Learning Research, an early open-access initiative that has become the field’s flagship journal.