Dr. Bernhard Schölkopf is a world-renowned computer scientist and pioneering figure in machine learning research. He currently serves as Director of the Department of Empirical Inference at the Max Planck Institute for Intelligent Systems in Tübingen, a position he has held since the institute's founding in 2011. Born in 1968 in Stuttgart, Schölkopf pursued interdisciplinary studies in physics, mathematics, and philosophy at universities in Tübingen and London, culminating in a doctorate in computer science from the Technical University of Berlin in 1997. His early career included research positions at the German National Research Center for Computer Science and industrial research stints at prestigious institutions including AT&T Bell Laboratories, Microsoft Research, and Biowulf Technologies.
Professor Schölkopf has made seminal contributions to the mathematical foundations of machine learning, particularly in kernel methods, learning theory, and causal inference. His groundbreaking work helped develop, advance, and generalize the theory of support vector machines, fundamentally shaping a critical area of machine learning methodology. His innovations in kernel PCA and kernel embeddings have advanced fundamental statistical methodology in dimensionality reduction, semi-supervised learning, and hypothesis testing, establishing new approaches widely adopted across scientific disciplines. Furthermore, his pioneering research in causal machine learning has created a novel understanding of learning causal relationships from data, with profound implications for scientific discovery across numerous fields.
Beyond his theoretical contributions, Schölkopf has played a critical leadership role in building the global machine learning community, serving as one of the founding directors of the Max Planck Institute for Intelligent Systems, which was established in 2011 through the transformation and expansion of the Max Planck Institute for Metals Research, and co-founding the European Laboratory for Learning and Intelligent Systems ELLIS. He established the influential Machine Learning Summer Schools that have educated generations of researchers and helped launch the Cyber Valley research consortium to foster innovation in artificial intelligence. His exceptional contributions have been recognized with numerous prestigious awards including the ACM AAAI Allen Newell Award, the Gottfried Wilhelm Leibniz Prize, and the Körber Prize, cementing his status as one of the world's most influential computer scientists. As a highly cited researcher and former editor of the Journal of Machine Learning Research, Schölkopf continues to shape the future direction of artificial intelligence research with his ongoing work at the intersection of machine learning and causal inference.
