Rianne de Heide


Department of Mathematics
NU building, room NU-9A13
Faculty of Science
Vrije Universiteit Amsterdam
De Boelelaan 1111, 1081 HV Amsterdam
E-mail: r.de.heide [at] vu [dot] nl (since I'm on maternity leave, I will read this e-mail again after February 1st)

About me

I am an assistant professor in the Department of Mathematics, at the Vrije Universiteit Amsterdam. I work on problems and solutions in machine learning and statistics. My research focuses on sequential learning, and in particular on (sequential) hypothesis testing, Bayesian learning and best-arm identification problems. Central in my work is both bringing a solid mathematical foundation to the topics I work on in different fields, as well as making the theory accessible for less mathematical audiences. I’m also interested in the mathematical and philosophical foundations of Bayesianism, machine learning, statistics and probability theory.

Find out more.

Veni grant

I am very happy that NWO (the Dutch Research Council) awarded my proposal “E-values for multiple testing” a Veni grant of 280.000 euros. With this I can conduct my own research for the coming 3 years. You can read about my research plans here: https://vu.nl/en/news/2023/veni-grant-for-rianne-de-heide-s-research-into-new-mathematical-theory

(Nederlands: https://vu.nl/nl/nieuws/2023/veni-beurs-voor-onderzoek-rianne-de-heide-naar-nieuwe-wiskundige-theorie)

Cor Baayen Award

I was awarded the 2023 Cor Baayen Early Career Researcher Award (news article). Since I'm on pregnancy/maternity leave at the moment, I will probably receive it and give a talk about my work in the ERCIM spring meeting in 2024.


Older News

  • I got tenure at the VU

  • I received the Willem R. van Zwet Award 2021 for my PhD thesis (news article, jury report)

More old news


My research interests include

  • Bandits, Reinforcement Learning

  • (Sequential) hypothesis testing, multiple testing

  • Group invariance in statistics

  • Bayesian methods

  • Learning theory

  • Imprecise probabilities in statistics

  • Foundations of ML, stats and probability theory

Find out more.

Recent Publications

  • Top Two Algorithms Revisited
    Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide and Emilie Kaufmann
    NeurIPS 2022    arxiv proc poster

  • The truth-convergence of open-minded Bayesianism
    Tom F. Sterkenburg and Rianne de Heide
    The Review of Symbolic Logic 15(1):64-100, 2022, doi:10.1017/S1755020321000022    philsci archive   proc