Bio: Formerly head of the machine learning group at CWI in Amsterdam, Peter Grünwald is currently member of CWI Management and full professor of statistics at the mathematical institute of Leiden University. He recently received an ERC Advanced Grant (2024) for designing a flexible theory of statistics, based on e-values and e-processes, the core concept in a novel, rapidly evolving theory he helped found with the breakthrough paper Safe Testing (arxiv 2019, now JRSS B) and extend in The E-Posterior (Phil. Trans. Roy. Soc. A, 2023) and Beyond Neyman-Pearson (PNAS 2024). 

From 2018-2022 Peter served as  President of the Association for Computational Learning, the organization running COLT, the world’s prime annual conference on machine learning theory, which he chaired in 2015, having earlier chaired UAI, another major ML conference. He is editor of  Foundations and Trends in Machine learning, author of the book (and standard reference) The Minimum Description Length Principle (MIT Press, 2007), and co-recipient of the Van Dantzig prize, the highest Dutch award in statistics and operations research. He has frequently appeared in Dutch national media commenting, e.g., about statistical issues in court cases. He has held a lifelong interest in, and published many papers on, the foundations of statistics