Some of the things I am doing / have been doing in the past

Short CV

  • Since 2015 Full professor for the theory of machine learning at the Department of Computer Science, University of Tübingen
  • 2012 - 2015 Full professor ("Heisenberg-Professor") for Machine Learning at the Department of Computer Science, University of Hamburg
  • 2007 - 2012 Research group leader for learning theory at the Max Planck Institute for Intelligent System, Tübingen, Germany
  • 2005 - 2006 Head of the Data Mining Group at Fraunhofer IPSI, Darmstadt, Germany.
  • 2002 - 2004 PhD student at the Department of Empirical Inference, Max Planck Institute for Biological Cybernetics, Tübingen.
  • 2001 Diplom (~ M.Sc.) in mathematics, after studying at the universities of Konstanz, Grenoble, and Tübingen

Short CV in English

Ulrike von Luxburg is a full professor for the Theory of Machine Learning at the University of Tuebingen, Germany. Her research is focused on statistical and theoretical aspects of unsupervised learning, in particular on learning algorithms on random graphs and networks and machine learning in a comparison-based framework. She is also coordinating a research consortium on Machine Learning in Science.

Kurzlebenslauf auf Deutsch

Ulrike von Luxburg ist Professorin für die Theorie des maschinellen Lernens an der Universität Tübingen und Sprecherin des Exzellenzclusters “Maschinelles Lernen: Neue Perspektiven für die Wissenschaft”. In ihrer Forschung untersucht sie beweisbare Garantien und theoretische Grenzen des maschinellen Lernens. In der öffentlichen Debatte engagiert sie sich auch zum Thema Ethik und gesellschaftliche Auswirkungen des maschinellen Lernens.

Foto / Picture

The following picture can be used in press (Copyright: University of Tübingen/ Christoph Jäckle).

Low resolution (700 kB; Copyright: University of Tübingen/ Christoph Jäckle):

Ulrike von Luxburg



High resolution (10 MB; Copyright: University of Tübingen/ Christoph Jäckle)

Ulrike von Luxburg


Here is a link to a short text version of this CV (in english and german) and a picture including copyright comments.

Scientific Awards

  • 2019 IJCAI Distinguished paper award
    Michael Perrot received the Distinguished Paper Award at IJCAI, the International Joint Conference on Artificial Intelligence, for our joint paper "Boosting for Comparison-Based Learning".
  • 2008 NIPS Best student paper award
    Markus Maier won the best student paper award for our joint paper at the Annual Conference on Neural Information Processing Systems (NIPS) 2008 pdf
  • 2008 German Young Academy
    I got appointed as a member of the "Junge Akademie", the young scientists' branch of the Berlin-Brandenburg Academy of Sciences and Humanities (Berlin-Brandenburgische Akademie der Wissenschaften - BBAW) and the German Academy of Natural Scientists Leopoldina (Deutsche Akademie der Naturforscher Leopoldina).
  • 2007 ALT Best student paper award
    Markus Maier won the best student paper award for our joint paper at the International Conference on Algorithmic Learning Theory (ALT), Sendai, Japan pdf
  • 2006 COLT best student paper award
    David Pal won an outstanding student award for our joint paper at the International Conference on Learning Theory (COLT), Pittsburgh, USA pdf
  • 2005 COLT best student paper award
    Matthias Hein won the outstanding student award paper for our joint paper at the International Conference on Learning Theory (COLT) 2005, Bertinoro, Italy pdf
  • 2004 NIPS best student paper award
    I won the outstanding student paper award at the Eighteenth Annual Conference on Neural Information Processing Systems (NIPS) 2004, Vancouver, Canada pdf
  • 2003 COLT best student paper award
    I won the best student paper award at the International Conference on Learning Theory (COLT) 2003, Washington, USA pdf

Community service

  • Since 2017 Executive board member of NeurIPS
  • 2017 -- 2019 Steering committee of the Association for Computational Learning (runs the COLT conference)
  • 2008 -- 2018 Action editor of JMLR
  • 2015 -- 2018 Board member of the International Machine Learning Society (runs the ICML conference)
  • 2017 General Chair of NIPS 2017, together with Isabelle Guyon.
  • 2016 Program chair of NIPS 2016, together with Isabelle Guyon. Here is a description on how we juggled the review process for 2500 submissions with 3500 reviewers. And our Exhibition of Rejected Papers.
  • 2011 Program Chair of COLT 2011 (together with Sham Kakade)
  • 2008 - 2013 member of Die Junge Akademie (German Young Academy), the young scientists branch of the German National Academy of Sciences.
  • 2007 - 2010 associate editor for Statistics and Computing

Workshops / summer schools I (co-)organized

  • 2016 Dagstuhl workshop "Foundations of Unsupervised Learning"
  • 2015 Workshop on learning theory at DALI, La Palma
  • 2015 Spring school "Structural Inference in Statistics'', March 2015, Sylt, Germany
  • 2013 Spring School on "Structural Inference in Statistics", Bad Belzig, Germany
  • 2012 Mini-Symposium "Machine Learning" at the Annual Meeting of the German Mathematical Society, Saarbrücken
  • 2011: NIPS workshop Relations between machine learning problems, Sierra Nevada, Spain
  • 2009: NIPS Workshop Clustering: Science or Art? Whistler, Canada
  • 2007: Workshop on Stability and Resampling Methods for Clustering, Tübingen, Germany
  • 2005: NIPS Workshop on Theoretical Foundations of Clustering, Whistler, Canada
  • 2003: Machine Learning Summer School (MLSS), Tübingen, Germany