Bernhard Schölkopf is a director at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany where he heads the Department of Empirical Inference. He is a leading researcher in the machine learning community where he is particularly active in the field of kernel methods. He has made particular contributions with support vector machines and kernel PCA. A large part of his work is the development of novel machine learning algorithms through their formulation as (typically convex) optimisation problems.

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. He has been program chair of COLT and NIPS and serves 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.