Hector Fellow since 2018
Prof. Dr. Bernhard Schölkopf

Prof. Dr. Bernhard Schölkopf

Max Planck Insti­tute for Intel­li­gent Systems, Tübin­gen site

Bernhard Schölkopf is direc­tor at the Max Planck Insti­tute for Intel­li­gent Systems, affil­i­ated profes­sor at ETH Zurich, and honorary profes­sor at the Univer­sity of Tübin­gen and TU Berlin.

He studies the detec­tion of regular­i­ties from obser­va­tional data. He has signif­i­cantly shaped the research field of machine learn­ing with his work on kernel methods, showing that a large range of learn­ing algorithms can be gener­al­ized to the nonlin­ear case and to non-vecto­r­ial data. More recently, he has combined machine learn­ing and causal infer­ence to develop new methods to recog­nize causal struc­tures (in addition to statis­ti­cal depen­dences) from obser­va­tional data.

Bernhard Schölkopf is a member of the German National Academy of Sciences (Leopold­ina) and has been awarded the Gottfried Wilhelm Leibniz Prize of the DFG (German Research Founda­tion), the Milner Award of the Royal Society, the BBAW Founda­tion Frontiers of Knowl­edge Award, and the Koeber European Science Award.

Max-Planck-Institut Multidisziplinare Naturwissenschaften - Biophysische Chemie
Doctor­ate Currently not vacant

Bernhard Schölkopf is currently unavail­able to super­vise doctoral projects.

Forschungsfeld Informatik

— Infor­mat­ics

Forschungsfeld Physik

— Physics

Forschungsfeld Mathematik

— Mathe­mat­ics

Infor­mat­ics, Physics, Mathematics

Research Fields

Machine learn­ing
Causal Infer­ence
Statis­ti­cal learn­ing theory