Germany - 2022
In recognition of his widely used research in machine learning, advancing both mathematical foundations and a broad range of applications in science and industry
Professor Bernhard Schölkopf is a world leader in machine learning, and has made seminal contributions to kernel methods, learning theory, and causality. Professor Schölkopf helped develop, advance, and generalize the theory of support vector machines, which has had a profound impact on machine learning. His contributions to kernel PCA and kernel embeddings have advanced fundamental statistical methodology in dimensionality reduction, semi-supervised learning, and hypothesis testing. Besides his theoretical and algorithmic contributions, Professor Schölkopf and his team have advanced numerous areas of applied machine learning, including applications to astronomy, biology, computer vision, robotics, neuroscience, and cognitive science. Professor Schölkopf?s pioneering work in causal machine learning has laid the foundation for a novel understanding of learning causal relationships from data, with implications for all areas of science.
Apart from his fundamental contributions to science, Professor Schölkopf has played a critical leadership role in the global and especially European AI and machine learning community. He founded the Max Planck Institute for Intelligent Systems, and the European Laboratory for Learning and Intelligent Systems (ELLIS), two power-houses of ML research. He co-founded the Machine Learning Summer Schools, which have educated many generations of ML researchers, and the Cyber Valley research consortium fueling entrepreneurial advances. He has served as EIC for JMLR and is among the world?s most cited computer scientists. His work has been honored with the Royal Society Milner Award and the BBVA Foundation Frontiers of Knowledge Award.