Ass.-Prof. Mag. Lukas Steinberger Bakk. BA, PhD

I am a tenure-track Assistant Professor for Statistical Machine Learning in the Department of Statistics and Operations Research at the University of Vienna and part of the research network Data Science @ Uni Vienna. Prior to that I was a post-doctoral researcher in the group of Angelika Rohde at the University of Freiburg and a temporary Full Professor in the Department of Mathematics at the Technical University of Munich.


My main research areas are statistical inference under differential privacy, high-dimensional data analysis, predictive inference and model selection. Please see my CV for further information.


  • Butucea, C. and Rohde, A. and Steinberger, L. (2023). Interactive versus non-interactive locally differentially private estimation: Two elbows for the quadratic functional. Annals of Statistics 51(2), 464--486, arXiv:2003.04773
  • Steinberger, L. and Leeb, H. (2023). Conditional predictive inference for stable algorithms. Annals of Statistics 51(1), 290--311, arXiv:1809.01412
  • Leeb, H. and Steinberger, L. (2023). Statistical inference with F-statistics when fitting simple models to high-dimensional data. Econometric Theory 39, 1249--1272, arXiv:1902.04304
  • Rohde, A. and Steinberger, L. (2020). Geometrizing rates of convergence under local differential privacy constraints. Annals of Statistics 48(5), 2646--2670, arXiv:1805.01422
  • Bachoc, F. and Preinerstorfer, D. and Steinberger, L. (2020). Uniformly valid confidence intervals post-model-selection. Annals of Statistics 48(1), 440--463, arXiv:1611.01043
  • Steinberger, L. and Leeb, H. (2019). Prediction when fitting simple models to high-dimensional data. Annals of Statistics 47(3), 1408--1442. pdf
  • Steinberger, L. and Leeb, H. (2018). On conditional moments of high-dimensional random vectors given lower-dimensional projections. Bernoulli 24(1), 565--591. pdf
  • Steinberger, L. (2016). The relative effects of dimensionality and multiplicity of hypotheses on the F-test in linear regression. Electronic Journal of Statistics 10, 2584--2640. doi:10.1214/16-EJS1186
  • Reschenhofer, E. and Preinerstorfer, D. and Steinberger, L. (2013). Non-monotonic penalizing for the number of structural breaks. Computational Statistics 28, 2585--2598. pdf


  • Amann, N. and Leeb, H. and Steinberger, L. (2024). Assumption-lean conditional predictive inference via the Jackknife and the Jackknife+. arXiv:2312.14596
  • Kalinin, N. and Steinberger L. (2024). Efficient estimation of a Gaussian mean with local differential privacy. arXiv:2402.04840
  • Steinberger, L. (2023). Efficiency in local differential privacy. arXiv:2301.10600
  • Steinberger, L. and Leeb, H. (2016). Leave-one-out prediction intervals in linear regression models with many variables. arXiv:1602.05801

Conference and seminar invitations

  • Lunch Seminar, ENSAE, Palaiseau, November 8, 2022.
  • Tenure Track Talks, Machine Learning – a multidisciplinary endeavor, University of Vienna, April 29, 2022.
  • JSM, Session ‘Challenges and Recent Advances in Private Data Analysis’, Seattle (online), August 9, 2021.
  • 10th Bernoulli-IMS World Congress, Session ‘Privacy’, Seoul (online), July 19, 2021.
  • CMStat, Session `Statistical problems under privacy constraints', London (online), December 20, 2020.
  • CMStat, Session `Recent developments in privacy-preserving data analysis', London, December 14-16, 2019.
  • Statistics Seminar, DPMMS, University of Cambridge, June 7, 2019.
  • Seminar `Statistics and Risk Management', Technical University of Munich, June 5, 2019.
  • KASTEL, Karlsruhe Institute of Technology, March 1, 2019.
  • Workshop on `Mathematical Foundations of Statistical Uncertainty Quantification', Freiburg, February 18, 2019.
  • Three part guest-lecture on `Statistical estimation under differential privacy', Ruhr-University Bochum, January 14–16, 2019.
  • Meeting in Mathematical Statistics, Fréjus, December 18, 2018.
  • FDM Seminar, University of Freiburg, November 9, 2018.
  • MSRaI Workshop, Vienna, July 14, 2018.
  • MFO, Oberwolfach, Workshop on `Matrix estimation meets statistical network analysis', June 18, 2018.
  • CFE-CMStat, Session `Model Selection and Inference', London, December 17, 2017.
  • Statistics Colloquium, TU Wien, Vienna, December 6, 2017.
  • IMT, Université Paul Sabatier, Toulouse, October 18, 2016.
  • Workshop on Model Selection, KU Leuven, September 8, 2016.

u:cris Portal

more information about my research activities
at the Univeristy of Vienna → u:cris