Prof. Dr. Bernhard Schölkopf

Adresse: Spemannstr. 38
72076 Tübingen
Raum Nummer: 211
Tel.: 07071 601 551
Fax: 07071 601 552
E-Mail: bernhard.schoelkopf


Bild von Schölkopf, Bernhard, Prof. Dr.

Bernhard Schölkopf

Position: Direktor  Abteilung: Schölkopf

Note: We have moved to the MPI for Metals Research and are in the process of reorienting it into an MPI for Intelligent Systems (working title). For a press release in German, click here.


My scientific interests are in the field of inference from empirical data, in particular machine learning and perception, and I am head of the Department of Empirical Inference. In particular, I study kernel methods for extracting regularities from high-dimensional data. These regularities are usually statistical ones, however, in recent years I have also become interested in methods for finding causal regularities.

To learn more about our work, you may want to take a look at the Department Overview from the last report to our scientific advisory board, or at short project reports from the same document:


Many of the papers can downloaded if you click on the tab "publications;" the older ones usually from A starting point is the first chapter of our book Learning with Kernels, available online. If your interest in machine learning is a mathematical one, you might prefer our review paper in the Annals of Statistics (arXiv link). For a general audience, I wrote a short high-level introduction in German that appeared in the Jahrbuch of the Max Planck Society.

Click here for a photograph of a beautiful northern light, which I took a few years ago from the plane on the way home from NIPS.

Note: I am not very organized with my e-mail; if you want to apply for a position in my lab, please send your application only to

Bernhard Schölkopf was born in Stuttgart on 20 February, 1968. He received an M.Sc. in mathematics and the Lionel Cooper Memorial Prize from the University of London in 1992, followed in 1994 by the Diplom in physics from the Eberhard-Karls-Universität, Tübingen. Three years later, he obtained a doctorate in computer science from the Technical University Berlin. His thesis on Support Vector Learning won the annual dissertation prize of the German Association for Computer Science (GI). In 1998, he won the prize for the best scientific project at the German National Research Center for Computer Science (GMD). He has researched at AT&T Bell Labs, at GMD FIRST, Berlin, at the Australian National University, Canberra, and at Microsoft Research Cambridge (UK). He has taught at Humboldt University, Technical University Berlin, and Eberhard-Karls-University Tübingen. In July 2001, he was appointed scientific member of the Max Planck Society and director at the MPI for Biological Cybernetics; in October 2002, he was appointed Honorarprofessor for Machine Learning at the Technical University Berlin. In 2006, he received the J. K. Aggarwal Prize of the International Association for Pattern Recognition, in 2011, he got the Max Planck Research Award. The ISI lists him as a highly cited researcher. He served on the editorial boards of JMLR, IEEE PAMI, and IJCV.

He is on the boards of the NIPS foundation and of the International Machine Learning Society. Members of his department have won various awards at the major machine learning conference.
Some details:

Journal of Machine Learning Research is an online journal which he helped launch as a founding action editor in early 2000. JMLR is the flagship journal of machine learning.
International Journal of Computer Vision
, one of the two flagship journals of computer vision (with IEEE PAMI, see below)
IEEE Transactions on Pattern Analysis and Machine Intelligence

Information Science and Statistics
, a Springer series of monographs
Advances in Data Analysis and Classification

With 5-year impact factors (ISI, 2008) of 10.3 and 8.0, respectively, IJCV and PAMI are the two top journals in the general area of artificial intelligence (they are ranked three and five in all of computer science). JMLR is number four (5.9).

In addition, he has served and serves as PC member (e.g., NIPS, COLT, ICML, UAI, DAGM, CVPR, Snowbird Learning Workshop) and as (program) (co-)chair of various conferences (COLT'03, DAGM'04, NIPS'05 (click here for NIPS'05 author and reviewer information), as well as the first two kernel workshops). He acted as general chair of NIPS'06.

Referenzen pro Seite: Jahr: Medium:

Zeige Zusammenfassung

Vorträge (30):

Seeger M, Nickisch H, Pohmann R und Schölkopf B (November-20-2008) Invited Lecture: Bayesian Optimization of Magnetic Resonance Imaging Sequences, Workshop Machine Learning Approaches to Representational Learning and Recognition in Vision, Frankfurt a.M., Germany.
Hofmann M, Steinke F, Aschoff P, Lichy M, Brady M, Schölkopf B und Pichler BJ (Oktober-25-2008) Abstract Talk: MR-Based PET Attenuation Correction: Initial Results for Whole Body, Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC 2008), Dresden, Germany.
Steinke F, Hein M und Schölkopf B (Juni-2008) Invited Lecture: Thin-Plate Splines Between Riemannian Manifolds, Workshop on Geometry and Statistics of Shapes 2008, Bonn, Germany.
Wichmann FA, Kienzle W, Schölkopf B und Franz MO (März-5-2008) Abstract Talk: Center-surround patterns emerge as optimal predictors for human saccade targets, 50. Tagung Experimentell Arbeitender Psychologen (TeaP 2008), Marburg, Germany.
Schweikert G, Zeller G, Weigel D, Schölkopf B und Rätsch G (Dezember-8-2007) Abstract Talk: Machine Learning Algorithms for Polymorphism Detection, NIPS 2007 Workshop on Machine Learning in Computational Biology (MLCB 2007), Whistler, BC, Canada.
Hofmann M, Steinke F, Scheel V, Brady M, Schölkopf B und Pichler BJ (September-2007) Abstract Talk: MR-Based PET Attenuation Correction: Method and Validation, AMI/SMI Joint Molecular Imaging Conference 2007, Providence, RI, USA(0013).
Schölkopf B (Juni-21-2007) Invited Lecture: Thoughts on Kernels, 17th Annual International Conference on Inductive Logic Programming (ILP 2007), Corvallis, OR, USA.
Martens SMM, Hill J, Farquhar J und Schölkopf B (Mai-2007) Invited Lecture: Impact of target-to-target interval on classification performance in the P300 speller, Scientific Meeting 2007 "Applied Neuroscience for Healthy Brain Function", Nijmegen, Netherlands.
Sun X, Janzing D und Schölkopf B (Dezember-2006): Inferring Causal Directions by Evaluating the Complexity of Conditional Distributions, NIPS 2006 Workshop on Causality and Feature Selection, Whistler, BC, Canada.
Farquhar J, Hill J und Schölkopf B (Dezember-2006): Learning Optimal EEG Features Across Time, Frequency and Space, NIPS 2006 Workshop on Current Trends in Brain-Computer Interfacing, Whistler, BC, Canada.
Hofmann M, Steinke F, Judenhofer MS, Claussen CD, Schölkopf B und Pichler BJ (November-2-2006) Abstract Talk: A Machine Learning Approach for Determining the PET Attenuation Map from Magnetic Resonance Images, IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC 2006), San Diego, CA, USA.
Schölkopf B (August-2006) Invited Lecture: Kernel Machines for Computer Graphics, 18th International Conference on Pattern Recognition (ICPR 2006), Hong Kong 38-39.
Schweikert G, Zeller G, Clark R, Ossowski S, Warthmann N, Shinn P, Frazer K, Ecker J, Huson D, Weigel D, Schölkopf B und Rätsch G (August-2006): Machine Learning Algorithms for Polymorphism Detection, 2nd ISCB Student Council Symposium at ISMB 2006, Fortaleza, Brazil.
Zhou D, Huang J und Schölkopf B (Dezember-10-2005) Invited Lecture: Beyond pairwise classification and clustering using hypergraphs, NIPS Workshop on Computational Biology and the Analysis of Heterogeneous Data (MLCB 2005), Whistler, BC, Canada.
Rätsch G, Sonnenburg S, Ong CS und Schölkopf B (Dezember-9-2005) Invited Lecture: Accurate prediction of alternative splicing events, NIPS Workshop on Computational Biology and the Analysis of Heterogeneous Data (MLCB 2005), Whistler, BC, Canada.
Hill NJ, Bensch M, Bogdan M, Lal TN, Rosenstiel W, Schölkopf B und Schröder M (Juni-16-2005) Abstract Talk: Machine-Learning Approaches to BCI in Tübingen, Third International Meeting on Brain–Computer Interface Technology (BCI 2005): Making a Difference, Rensselaerville, NY, USA.
Birbaumer N, Widmann G, Elger C, Schröder M, Hinterberger T, Lal TN, Schölkopf B, Tatagiba M und Freudenstein D (Februar-18-2005) Abstract Talk: Invasive and Non-Invasive Brain-Computer-Interfaces for Communication in Locked-In Syndrome, 6th Meeting of the German Neuroscience Society, 30th Göttingen Neurobiology Conference, Göttingen, Germany 239.
Schmid M, Henz S, Davison T, Pape U, Vingron M, Schölkopf B, Weigel D und Lohmann JU (Juli-12-2004) Abstract Talk: AtGenExpress: Expression atlas of Arabidopsis Development, 15th International Conference on Arabidopsis Research, Berlin. Germany 485.
Schölkopf B (September-8-2003) Invited Lecture: Kernel methods and dimensionality reduction, Designing Tomorrow' s Category-Level 3D Object Recognition Systems: An International Workshop, Taormina, Italy.
Schölkopf B (April-14-2003) Invited Lecture: Tutorial: introduction to kernel methods, Workshop "Kernel Methods in Computational Biology", Berlin, Germany.
Bousquet O und Schölkopf B (März-2003) Invited Lecture: Statistical Learning Theory, Interdisziplinäres Kolleg Günne 2003: Applications, Brains and Computers, Günne, Germany.
Besserve M, Schölkopf B, Logothetis NK und Panzeri S (Dezember-11-11) Abstract Talk: Causality analysis in information flow from cortical time series, NIPS 2011 Satellite Meeting on Causal Graphs: Linking Brain Structure to Function, Granada, Spain.

Patent (1):

Pichler B, Hofmann M, Schölkopf B und Steinke F: Method for determining a property map for an object in particular for a living being based on at least one first image in particular a nuclear magnetic resonance image, WO 2008006451 A1, (Juli-12-2006).
1, ... , 5, 6, 7, 8, 9, 10

Export als:
BibTeX, XML, pubman, Edoc, RTF
Last updated: Montag, 22.05.2017