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You are here: Home / Member News / Award Deadlines and Information / Rousseeuw Prize for Statistics Comes with $1M Award, Recognition

Rousseeuw Prize for Statistics Comes with $1M Award, Recognition

March 1, 2022 Leave a Comment

Mia Hubert and Stefan Van Aelst

    The King Baudouin Foundation—a large public utility foundation in Belgium—recently established the Rousseeuw Prize for Statistics, which comes with a $1 million award. Nominations will be accepted until March 31.

    Statistics is a cornerstone of science, health, industry, economics, and government; it benefits society as a whole. Nevertheless, research in statistics does not receive the same level of recognition as do related fields such as mathematics, physics, and computer science. The Rousseeuw Prize for Statistics, named after its sponsor—statistician Peter J. Rousseeuw—was created to remedy this gap.

    The prize will award pioneering work in statistical methodology. It is for an outstanding contribution or tool that has had significant impact and found wide application in statistical practice, with relevance to society.

    The prize focuses on the innovation, rather than an individual, allowing for recognition of several people who made significant contributions.

    The prize of $1 million will be awarded in even years, starting in 2022, and will be split among all honorees. The first award ceremony is scheduled for November 2022 at the University of Leuven, Belgium.

    For the purpose of the prize, statistics is defined as “the science and technology of obtaining useful information from data, taking its variability into account.” Statistical work in the above sense can be found under a variety of flags, such as astrostatistics, big data, biometrics, chemometrics, classification, data analysis, data collection, data mining, data science, data visualization, design of experiments, econometrics, environmetrics, genomic statistics, machine learning, multivariate analysis, pattern recognition, psychometrics, quality assurance, quantitative finance, regression, sociometrics, statistical computing, statistical learning, technometrics, time series analysis, etc.

    A rough subdivision of the statistics field will be considered: (1) general statistical methodology; (2) computational statistics and data science; (3) biostatistics and environmetrics; (4) statistics in the physical sciences and industry; and (5) statistics in economics and humanities.

    The King Baudouin Foundation appoints an international Selection Committee (SC) consisting of 10 reputed statisticians. The SC will make a ranked shortlist of three options in case some awardees do not accept the prize or are unwilling to be present at the award ceremony. To avoid undue pressure on the SC, its members are anonymous while they do their work. When the award is announced, the identities of the SC members whose terms have ended will be communicated.

    When selecting the award topic and awardees, the SC will consider important contributions and contributors irrespective of gender, race, sexual orientation, ideology, or religion.

    Nominations should propose a particular innovation and a list of important contributors. When making this list, applicants should consider gender diversity when applicable. Self-nomination is not permitted. Nominations, including letters of recommendation, are to be submitted by March 31.

    Filed Under: Award Deadlines and Information Tagged With: astrostatistics, big data, Biometrics, biostatistics and environmetrics, chemometrics, classification, computational statistics and data science, data analysis, data collection, data mining, data science, data visualization, design of experiments, econometrics, economics, environmetrics, general statistical methodology, genomic statistics, government, health, Industry, machine learning, multivariate analysis, pattern recognition, Peter J. Rousseeuw, psychometrics, quality assurance, quantitative finance, regression, science, sociometrics, Statistical Computing, statistical learning, statistics in economics and humanities, statistics in the physical sciences and industry, technometrics, time series analysis

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