Keywords: causality, machine learning, Earth system science, distribution generalization, policy learning, independence testing.
Most of the publications are also on Google Scholar.
Please always add a CV and your transcripts when asking for supervision of a thesis. Also, we receive a lot of requests for supervising theses; my apologies that I cannot agree to all of such requests.
There may be an open position announced later this year. All details can be discussed during the application process. My apologies that I cannot answer to all individual emails before the deadline.
Currently, I am AEing for IEEE Transactions on Pattern Analysis and Machine Intelligence (since Jan 2021) and the Journal of Causal Inference (since Jan 2021). (In the past, I have also AE'd for Annals of Statistics, the Journal of the American Statistical Association and SIAM Journal on Mathematics of Data Science.) My apologies that I have to decline most of the additional review requests.
We have written a book on mathematical games that will appear at MIT Press.
Jonas Peters, Nicolai Meinshausen: The Raven's Hat: Fallen Pictures, Rising Sequences, and Other Mathematical Games
Jim Stein has asked us a few questions about our book `The Raven's Hat'. Click here if you are interested in the interview.
We have written a book on causality that has appeared as open access at MIT Press. In July 2018, it was awarded the ASA causality in statistics education award.
Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Elements of Causal Inference: Foundations and Learning Algorithms
The pdf can be downloaded for free from the MIT Press website (look for "This is an open access title" on the left-hand side).
We have created a few notebooks for getting to know causality. They are available here.
I have written a script on causality. Almost all of it made it into our book. It is a bit shorter but less polished. It can be downloaded here.
Test of Time Award (runner-up) at ICML (with B. Scholkopf, D. Janzing, E. Sgouritsa, K. Zhang, and J. Mooij, 2022), Silver Medal of the Royal Danish Academy of Sciences and Letters (2021), COPSS Leadership Academy, awarded by the Committee of Presidents of Statistical Societies (2021), Guy Medal in Bronze, awarded by the Royal Statistical Society (2019), ASA Causality in Statistics Education Award (with D. Janzing and B. Sch\"olkopf, 2018), Teacher of the year at SCIENCE, University of Copenhagen (2018), Read paper to the Royal Statistical Society, London (with P. B\"uhlmann and N. Meinshausen, 2016), Member of the Junge Akademie (2016--2021; board member 2017--2019), Marie Curie fellowship (2013--2015), ETH medal for an outstanding PhD thesis (2013), Scholarhsip of the Studienstiftung des deutschen Volkes (2004--2008), UNWIN prize and election to scholar (Downing College, University of Cambridge, 2007), European Excellence Programme (DAAD, 2006--2007), Kurt-Hahn-Trust (2006--2007), Holderlin Programme (Allianz, 2006--2007), Deutsche SchulerAkademie (2001).
Jonas is interested in using different types of data to predict the effect of interventions and to build statistical methods that are robust with respect to distributional shifts. He seeks to combine theory and methodology and tries to let real world applications guide his research. His work relates to areas such as causal inference, distribution generalization, dynamical systems, policy learning, graphical models, and independence testing. Since 2023, Jonas is professor in statistics at ETH Zurich. Previously, he has been a professor at the Department of Mathematical Sciences at the University of Copenhagen and a group leader at the Max-Planck-Institute for Intelligent Systems in Tuebingen. He studied Mathematics at the University of Heidelberg and the University of Cambridge and obtained his PhD jointly from MPI and ETH.
His full CV is available here (version: November 2021).