Note: Dominik Janzing has transitioned from the institute (alumni).
Research interests:
- novel causal inference methods and their foundation
- physics of causality and information flow
- notions of complexity and their application in machine learning
- statistical methods
- statistical physics, in particular the link between causality and the second law of thermodynamics.
I founded the group "causal inference" together with Bernhard Schölkopf. The website can be found here
We (Jonas Peters, Bernhard Schölkopf, and me) have written a book on causal inference.
I have been working on quantum information theory for many years and I'm still interested in it; my current causality research is strongly influenced by the paradigm that information is physical. In 2003, I started a project on causal inference together with the student Xiaohai Sun at the Universitaet Karlsruhe (meanwhile KIT), which later resulted in a joint project with the MPI for Biological Cybernetics and thus became the beginning of the causality group. My new website can be found here.
From there you find also my complete publication list.Dominik Janzing studied physics in Tübingen (Germany) and Cork (Ireland) and received a Ph.D. in mathematics from the Unversity of Tübingen in 1998. From 1998-2006 he was a postdoc and senior scientist at the Computer Science department of the University of Karlsruhe (TH) where he worked on quantum thermodynamics, quantum control, as well as quantum complexity theory and its physical foundations. In 2006 he received his teaching permission (Habilitation) from the Computer Science Department at Universität Karlsruhe (now "Karlsruhe Institute of Technology (KIT)"). Since 2007 he has been working as a senior scientist at the Max Planck Institute for Biological Cybernetics in Tübingen, where he founded the group causal inference together with Bernhard Schölkopf.
The group develops novel methods for causal reasoning from statistical data. These novel approaches use complexity of conditional probability distributions for causal reasoning. The idea is strongly influenced by his previous work on complexity of physical processes and the thermodynamics of information flow.