My scientific interests are in the field of machine learning and inference from empirical data. This is usually based on statistical regularities, however, I take a particular interest in causal structures that underlie statistical dependences.

I have worked on a number of different applications of machine learning - in our field, you get "to play in everyone's backyard." For instance, 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 last formal Research Overview and Alumni List.

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

• Arxiv overview paper on causality for machine learning, recommended by Judea Pearl
• More recent causality review written for the International Congress of Mathematicians
• Book about causality, published as an open access title at MIT Press (PDF, with Jonas Peters and Dominik Janzing).
• Exoplanets we have discovered; one of them (K2-18b) recently made the news as the first habitable zone exoplanet whose atmosphere contains water. CIFAR news article.
• Some of my photographs: HDR composite of the 2019 solar eclipse viewed from La Silla, including the moon lit by the earth, wide angle view; 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, taken 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, and have often seen northern lights. Looking at the night sky is a fascinating and humbling experience.
• Some chapters of our book Learning with Kernels.
• Review paper on kernel methods in the Annals of Statistics.
• Short high-level introduction on statistical learning theory (in German) that appeared in the 2004 Jahrbuch of the Max Planck Society.
• Obituary for Alexej Chervonenkis (NIPS 2014).
• I am a member of the LIGO scientific collaboration to detect gravitational waves
• With the growing interest in (how to make money with) big data, machine learning has significantly gained in popularity. We published an article in the German newspaper FAZ in January 2015, discussing some of the implications.  Disclaimer: the newspaper added some text that appears above our names - this was not written or approved by us.
• In March 2018, I published an article about the cybernetic revolution in the German newspaper SZ. It starts by pointing out that the current revolution is about processing (generating, converting, industrializing) information in much the same way the first two industrial revolutions dealt with processing (generating, converting, industrializing) energy. I have occasionally put forward this thesis (but I assume I am not the only one who thinks of it this way), for instance during a NYU symposium on the future of AI in January 2016 (here are some notes written by Max Tegmark), and in some more detail in section two of this arxiv paper. The article also provides recommendations on what Europe should do to keep up with the development.
• A children's book
• I do not engage in military research, and I believe AI/ML should not be used for aggressive military purposes. Open letter against autonomous AI weapons / open letter against a military collaboration of KAIST, with positive outcome / IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems
• My department and/or members of the department (incl. myself) receive funding from a number of sources including Max Planck, DFG, Alexander-von-Humboldt foundation, BMBF (German Ministry of Science), Amazon, EU, ETH Zürich, the federal state of Baden-Wuerttemberg, Google, Bosch, Facebook, Hector foundation, Koerber foundation, CIFAR, and the Stanford Center on Philanthropy and Civil Society.
• 53839 Scholkopf (2000 EY197)

Machine Learning Causal Inference Artificial Intelligence Computational Photography Statistics