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Researcher · Executive
Bernhard Schölkopf
Max Planck Institute for Intelligent SystemsDirector, Department of Empirical Inference
ELLISScientific Director, ELLIS Institute Tübingen
🇩🇪 GermanBorn 1968
Schölkopf helped establish kernel methods, an influential way for computers to find complex patterns in data. He later became a leading figure in causal learning, which tries to separate genuine cause and effect from mere correlation, with applications across scientific discovery.[1]
Career & education
Current rolesMax Planck Institute for Intelligent Systems2011-presentDirector, Department of Empirical InferenceELLIS2023-presentScientific Director, ELLIS Institute Tübingen
Max Planck Institute for Intelligent Systems2011-presentELLIS2023-presentPreviously
Work and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations301,164As of Nov 1, '26
citations+4,299Since last snapshot, Oct 1, '26
Selected contributions
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
With Alex SmolaA book explaining kernel methods for learning complex patterns by comparing examples.
References
- Max Planck Society — kernel methods and causal learningmpg.de
Schölkopf helped establish kernel methods, an influential way for computers to find complex patterns in data. He later became a leading figure in causal learning, which tries to separate genuine cause and effect from mere correlation, with applications across scientific discovery.
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Reviewed August 8, 2026 · Checked for accuracy and new information.
