Katarzyna Reluga

Katarzyna Reluga

Lecturer (Assistant Professor)

University of Bristol


I am a Lecturer (Assistant Professor) in the School of Mathematics at the University of Bristol, affiliated with the Institute for Statistical Science. Prior to joining the University of Bristol, I did postdocs at the University of California, Berkeley, the University of Toronto, and the University of Cambridge, where I worked with Mark van der Laan, Dehan Kong, and Qingyuan Zhao, respectively. I completed my PhD in the University of Geneva, where I was advised by Stefan Sperlich and co-advised by María José Lombardía.

My research interest lies at the intersection of survey methodology, causal inference and machine learning. During my PhD I worked on theoretical aspects of simultaneous, post-selection and computational inference with some applications in economics and social sciences. Afterwards, I broadened my research agenda by trying to solve some open problems in causal inference and merging machine learning with survey sampling methodology.

Pronouns: she/her

  • Causal Inference
  • Machine Learning
  • Mixed and Multilevel Models
  • Resampling Techniques
  • Survey Statistics
  • Ph.D. in Statistics, 2020

    University of Geneva

  • M.S. in Statistics, 2016

    KU Leuven

  • Exchange Student, 2016

    ETH Zurich

  • B.S. in Quantitative Methods in Economics and Information Systems, 2014

    Warsaw School of Economics

  • B.A. in Modern Languages, 2014

    University of Warsaw

Publications & Preprints

(2022). Simultaneous inference for linear mixed model parameters with an application to small area estimation. International Statistical Review.

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(2021). Simultaneous inference for empirical best predictors with a poverty study in small areas. Journal of the American Statistical Association.

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