{"title":"A Conversation With Marc Hallin","authors":"Christian Genest","doi":"10.1111/insr.12576","DOIUrl":null,"url":null,"abstract":"<p>Marc Hallin was born in Ghent, Belgium, on 23 April 1949. He holds a <i>Licence en Sciences mathématiques</i> (1971), a <i>Licence en Sciences actuarielles</i> (1972), and a <i>Doctorat en Sciences</i> (1976) from the <i>Université libre de Bruxelles</i>. He then rose through the professorial ranks at the same institution, being successively <i>Premier Assistant</i> (1977–1978), <i>Chargé de Cours associé</i> (1978–1984), <i>Chargé de Cours</i> (1984–1988), <i>Professeur ordinaire</i> (1988–2009), and <i>Professeur ordinaire émérite</i> upon retirement in 2009. Throughout his career, he supervised 25 PhD students and held invited positions at many institutions of high standing in Austria, Belgium, England, France, Hong Kong, Italy, Portugal, Spain, Switzerland, and the USA (most notably Princeton). A renown expert in time series analysis, econometrics, and non-parametric inference, Marc is the author or coauthor of over 250 research papers, for which he received numerous awards, including the Medal of the Faculty of Mathematics and Physics of Charles University in Prague (2006), a <i>Humboldt Forschungspreis</i> from the Alexander von Humboldt Foundation (2012), the Pierre-Simon de Laplace Award of the <i>Société française de Statistique</i> (2022), and the Gottfried E. Noether Distinguished Scholar Award of the American Statistical Association (2022). He gave several distinguished lecture series, including the 2017 Hermann Otto Hirschfeld Lecture Series at the <i>Humboldt Universität zu Berlin</i>, and the 2018 Mahalanobis Memorial Lecture at the Indian Statistical Institute. Over the years, he co-edited a dozen books and proceedings, and served on the editorial boards of several journals, including the <i>Journal of Time Series Analysis</i> (1994–2009), the <i>Journal of Econometrics</i> (2013–2019), the <i>Journal of Business and Economic Statistics</i> (2018–), and the Theory and Methods Section of the <i>Journal of the American Statistical Association</i> (2005–). He is a Fellow of the Institute of Mathematical Statistics (1990) and the American Statistical Association (1997), as well as a member of the <i>Classe des Sciences</i> of the Royal Academy of Belgium (1999). Marc has been a member of the International Statistical Institute since 1985 and was (co-) Editor-in-Chief of the <i>International Statistical Review</i> from 2010 to 2015.</p>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/insr.12576","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Statistical Review","FirstCategoryId":"100","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/insr.12576","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
Marc Hallin was born in Ghent, Belgium, on 23 April 1949. He holds a Licence en Sciences mathématiques (1971), a Licence en Sciences actuarielles (1972), and a Doctorat en Sciences (1976) from the Université libre de Bruxelles. He then rose through the professorial ranks at the same institution, being successively Premier Assistant (1977–1978), Chargé de Cours associé (1978–1984), Chargé de Cours (1984–1988), Professeur ordinaire (1988–2009), and Professeur ordinaire émérite upon retirement in 2009. Throughout his career, he supervised 25 PhD students and held invited positions at many institutions of high standing in Austria, Belgium, England, France, Hong Kong, Italy, Portugal, Spain, Switzerland, and the USA (most notably Princeton). A renown expert in time series analysis, econometrics, and non-parametric inference, Marc is the author or coauthor of over 250 research papers, for which he received numerous awards, including the Medal of the Faculty of Mathematics and Physics of Charles University in Prague (2006), a Humboldt Forschungspreis from the Alexander von Humboldt Foundation (2012), the Pierre-Simon de Laplace Award of the Société française de Statistique (2022), and the Gottfried E. Noether Distinguished Scholar Award of the American Statistical Association (2022). He gave several distinguished lecture series, including the 2017 Hermann Otto Hirschfeld Lecture Series at the Humboldt Universität zu Berlin, and the 2018 Mahalanobis Memorial Lecture at the Indian Statistical Institute. Over the years, he co-edited a dozen books and proceedings, and served on the editorial boards of several journals, including the Journal of Time Series Analysis (1994–2009), the Journal of Econometrics (2013–2019), the Journal of Business and Economic Statistics (2018–), and the Theory and Methods Section of the Journal of the American Statistical Association (2005–). He is a Fellow of the Institute of Mathematical Statistics (1990) and the American Statistical Association (1997), as well as a member of the Classe des Sciences of the Royal Academy of Belgium (1999). Marc has been a member of the International Statistical Institute since 1985 and was (co-) Editor-in-Chief of the International Statistical Review from 2010 to 2015.
期刊介绍:
International Statistical Review is the flagship journal of the International Statistical Institute (ISI) and of its family of Associations. It publishes papers of broad and general interest in statistics and probability. The term Review is to be interpreted broadly. The types of papers that are suitable for publication include (but are not limited to) the following: reviews/surveys of significant developments in theory, methodology, statistical computing and graphics, statistical education, and application areas; tutorials on important topics; expository papers on emerging areas of research or application; papers describing new developments and/or challenges in relevant areas; papers addressing foundational issues; papers on the history of statistics and probability; white papers on topics of importance to the profession or society; and historical assessment of seminal papers in the field and their impact.