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Peter Grünwald heads the machine learning group at CWI in Amsterdam, the Netherlands. He is also full professor of Statistical Learning at the mathematical institute of Leiden University.  From 2018-2022 he served as the President of the Association for Computational Learning, the organization running COLT, the world’s prime annual conference on machine learning theory. He was co-program chair of COLT in 2015 and chaired UAI – another top ML conference – in 2010/2011. Apart from publishing at top ML venues like NeurIPS, COLT and UAI, he regularly contributes to top statistics journals as well. He is the author of the book (and standard reference) The Minimum Description Length Principle, (MIT Press, 2007; see here for an up-to-date (2020), much shorter introduction). In 2010 he was co-awarded the Van Dantzig prize, the highest Dutch award in statistics and operations research. He received NWO VIDI (2005), VICI (2010) and TOP-1 (2016) grants.

Peter’s research currently focuses on Safe, Anytime-Valid Inference based on the emerging theory of e-values and e-processes. E-values are an alternative to p-values that effortlessly deal with optional continuation: with e-value based tests and the corresponding always valid confidence intervals, one can always gather additional data, while keeping statistically valid conclusions. Until June 2019, publications on e-values were few and far between: the concept did not even have a name. Then, in the course of just six months, four papers by different research groups appeared on arXiv that firmly established them as an important statistical concept, leading to a plethora of novel results. Recent publications and preprints include:

Introductions/Overviews/General Methodology:

  • G. and Rianne de Heide and Wouter Koolen. Safe Testing. Accepted for publication in the Journal of the Royal Statistical Society, Series B, 2023 (arXiv version). The original arXiv version (which has been very, very substantially revised) is the first (2019) paper in which e-values were given a name (originally we called them s-value).
  • G., 2023. The E-Posterior. Philosophical Transactions of the Royal Society of London Series A, 2023 (arXiv version) ;  G., 2023, Beyond Neyman-Pearson (under submission; arXiv version). Together these two papers put forward a novel approach to statistical inference that provides a middle ground between (and is different from both) standard Bayesian and frequentist approaches.
  • A. Ramdas, G., V. Vovk, G. Shafer Game-theoretic statistics and safe anytime-valid inference (SAVI). Statistical Science, 2023. (arXiv version). The first overview paper of this exciting new area, written by some of its most prolific contributors (each involved in one of the four initial 2019 papers).

Development of Specific E-Values and Applications:

  • G., Alexander Henzi, Tyron Lardy. Anytime Valid Tests of Conditional Independence Under Model-X . Journal of the American Statistical Association,  2023. (arXiv version).
  • Rosanne Turner and G. Safe Sequential Testing and Effect Estimation in Stratified Count Data (arXiv version), Proceedings 26th Intern. Conf. on AI and Statistics (AISTATS) 2023, Valencia, Spain, 2023 (among the 2.5% of submissions selected for oral presentation).
  • Judith ter Schure and G. ALL-IN meta-analysis: Breathing life into living systematic reviews. F1000Research, Volume 11 p. 549.1- 549.24. Here is a general CWI project page with info about ALL-IN meta-analysis based on e-values and e-processes.
  • Judith ter Schure, A. Ly, <many others>, G. H. van Werkhoven. Bacillus Calmette-Guérin vaccine to reduce COVID-19 infections and hospitalisations in healthcare workers – a living systematic review and prospective ALL-IN meta-analysis of individual participant data from randomised controlled trials. medrxiv preprint, December 2022. This is the first time that the e-value based approach was (and is) actually used in a live meta-analysis.
  • Muriel Felipe Pérez-Ortiz, Tyron Lardy, Rianne de Heide, G.  E-Statistics, Group Invariance and Anytime Valid Testing. Under submission. (arXiv version), 2022.

Note: at the ML group at CWI we do not offer internships for master’s and bachelor’s students from outside of the Netherlands. We only have an international internship program for Ph.D. students that are in their second or later years (I get so many requests for internships these days that I cannot respond to each request individually).