Bernhard Schölkopf | Empirical Inference - Max Planck Institute for Intelligent Systems

Bernhard Schölkopf
Director

Empirical Inference

Office: N4.019
Spemannstr. 34
72076 Tübingen
Germany

+49 7071 601 551

+49 7071 601 552

My scientific interests are in the field of machine learning and inference from empirical data. In particular, I study kernel methods for extracting regularities from possibly high-dimensional data. These regularities are usually statistical ones, however, in recent years I have also become interested in methods for finding causal structures that underly statistical dependences. I have worked on a number of different applications of machine learning - in data analysis, you get "to play in everyone's backyard." Most recently, I have been trying to play in the backyard of astronomers and photographers.

I am heading the Department of Empirical Inference; take a look at our Research Overview and Alumni List.

Many of my papers can downloaded if you click on the tab "publications;" alternatively, from http://www.kernel-machines.org/ or from arxiv. Some additional links:

Some chapters of our book Learning with Kernels.
Review paper on kernel methods in the Annals of Statistics.
Short high-level introduction on statistical learnig theory (in German) that appeared in the 2004 Jahrbuch of the Max Planck Society.
Obituary for Alexej Chervonenkis (NIPS 2014).
With the growing interest in (how to make money with) big data, machine learning has significantly gained in popularity. We have published an article in the German newspaper FAZ, discussing some of the implications. Disclaimer: the text that appears above our names was neither written nor approved by us.
A children's book
Photographs: view of the Alps from the southern black forest, a rainbow in La Palma, a lunar eclipse in 2007, the Andromeda galaxy, the Milky Way on the Roque de los Muchachos, the North America Nebula, the constellation Orion with Barnard's loop, and finally a picture of a beautiful northern light, which I took a few years ago from the plane, on the way home from a conference in Vancouver. I always try to get a window seat when flying home from the North American west coast - it is surprizingly common to see northern lights. Looking at the night sky is a fascinating and humbling experience.
open letter against autonomous AI weapons

Machine Learning Causal Inference Artificial Intelligence Computational Photography Statistics

click here

M.Sc. in mathematics and Lionel Cooper Memorial Prize, University of London (1992)
Diplom in physics (Tübingen, 1994)
doctorate in computer science from the Technical University Berlin (1997); thesis on Support Vector Learning (main advisor: V. Vapnik, AT&T Bell Labs) won the annual dissertation prize of the German Association for Computer Science (GI)
scientific member of the Max Planck Society, 2001
awards won by his lab
J. K. Aggarwal Prize of the International Association for Pattern Recognition, 2006
Max Planck Research Award, 2011
Academy Prize of the Berlin-Brandenburg Academy of Sciences and Humanities, 2012
Royal Society Milner Award, 2014
Honorarprofessor at the Technical University Berlin (computer science) and at the Eberhard-Karls University Tübingen (physics)
list of publications as of January 2015
"ISI highly cited" (added in 2010)
the h Index for Computer Science
Google Scholar page
co-editor-in-chief of JMLR
board member, ACM Books
member of the boards of the NIPS foundation and of the International Machine Learning Society
PC member (e.g., NIPS, COLT, ICML, UAI, DAGM, CVPR, Snowbird Learning Workshop) and co-chair of various conferences (COLT'03, DAGM'04, NIPS'05, NIPS'06 and the first two kernel workshops).
co-founder of the Machine Learning Summer Schools
two-page CV: PDF.

If you'd like to contact me, please consider these two notes:

1. I recently became co-editor-in-chief of JMLR. I work for JMLR because I believe in its open access model, but it takes a lot of time. During my JMLR term, please don't convince me to do other journal or grant reviewing duties.

2. I am not very organized with my e-mail so if you want to apply for a position in my lab, please send your application only to Sekretariat-Schoelkopf@tuebingen.mpg.de. Note that we do not respond to non-personalized applications that look like they are being sent to a large number of places simultaneously.

We are always happy to receive outstanding applications for PhD positions and postdocs. In particular, we are looking for PhD students with interests in general machine learning (including kernel methods and causal inference) or computational imaging (photography, astronomy, MR).

626 results (BibTeX)

2017

Differentially Private Database Release via Kernel Mean Embeddings

Balog, M., Tolstikhin, I., Schölkopf, B.

2017 (conference) Submitted

Bernhard Schölkopf Director

2017

2017

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Bernhard Schölkopf
Director