Rianne de Heide

Teaching MLT 

Machine Learning Group,
Centrum Wiskunde en Informatica (CWI)
Science Park 123, Amsterdam
E-mail: r.de.heide [at] cwi [DOT] nl

Statistical Science Group
Mathematical Institute
Leiden University

About me

I am a PhD candidate at CWI under supervision of Peter Grünwald. I work on problems and solutions in machine learning and statistics, with a focus on Bayesian learning, hypothesis testing and sequential learning. In particular, I am interested in exploring the limitations of existing methods under misspecification of the model or the data collecting process, and in devising new, robust methods for these settings. Recently I became interested in pure exploration problems, which are problems in a bandit setting, dealing with the question how to design systems that efficiently explore their stochastic environment, with the goal of learning something specific about it, for example, best-arm identification.

Currently, I am visiting Alexandra Carpentier at the Otto von Guericke Universität in Magdeburg.

Until August 2020 I was a board member of the European Women in Mathematics – The Netherlands, the Dutch association of women professional mathematicians.

In spring 2019, I visited SequeL (Inria Lille-Nord Europe) on a LUF travel grant, to work with Emilie Kaufmann and Michal Valko.

Find out more.


My research interests include

  • Bandits, pure exploration problems

  • (Sequential) hypothesis testing

  • Group invariance in statistics

  • Bayesian methods

  • Learning theory

  • Foundations of ML, stats and probability theory

Find out more.

Recent Publications