David Rindt

David Rindt

Nonparametric measures of dependence

PhD student under Dino Sejdinovic and David Steinsaltz working on Nonparametric measures of dependence and variable selection. In particular I’m focussing on the Hilbert Schmidt independence criterion. We try to extend existing techniques to new types of data, such as censored data and rankings. I started my PhD in October 2017.



  • T. Fernandez , A. Gretton , D. Rindt , D. Sejdinovic , A Kernel Log-Rank Test of Independence for Right-Censored Data, Journal of the American Statistical Association, 2021.
  • D. Rindt , D. Sejdinovic , D. Steinsaltz , Consistency of permutation tests of independence using distance covariance, HSIC and dHSIC, Stat, vol. 10, no. 1, e364, 2021.


  • D. Rindt , D. Sejdinovic , D. Steinsaltz , A kernel and optimal transport based test of independence between covariates and right-censored lifetimes, International Journal of Biostatistics, 2020.


  • D. Rindt , D. Sejdinovic , D. Steinsaltz , Nonparametric Independence Testing for Right-Censored Data using Optimal Transport, ArXiv e-prints:1906.03866, 2019.