Paul Eilers
Paul Eilers is emeritus professor of biostatistics at Erasmus University Medical Center in Rotterdam (the Netherlands). He studied electronics and gradually got drawn into statistics and applied it in different fields: mechanical engineering, environmental modelling and protection, social science, medicine and genomics. He has a special interest in smoothing and visualization of data. He is an experienced R programmer and a co-author of packages on CRAN (JOPS, TwoTimeScales).
Patrick J. Groenen
Patrick J.F. Groenen is a professor of statistics at the Erasmus School of Economics (ESE). He currently is also dean of that school. His work focuses on data science techniques and their numerical algorithms. He is the co-author of several textbooks on multidimensional scaling published by Springer and has published articles in the top peer-reviewed journals including, among others, the Journal of Machine Learning Research, the Journal of Marketing Research, Psychological Methods, Psychometrika, the Journal of Classification, Computational Statistics and Data Analysis, the British Journal of Mathematical and Statistical Psychology, and the Journal of Empirical Finance. Amongst techniques that bears his interest are amongst others multidimensional scaling, regularized prediction methods, (convex) clustering, support vector machines, correspondence analysis, and majorization.
Trevor Hastie
Trevor Hastie is the John A Overdeck Professor of Statistics (emeritus) at Stanford University. His research is centered in applied statistics, particularly in the fields of statistical modeling and computing,
bioinformatics and machine learning. He has published seven books and over 200 research articles in these areas. Prior to joining Stanford University in 1994, Hastie worked at AT&T Bell Laboratories for nine
years, where he contributed to the development of the statistical modeling environment popular in the R computing system. He has contributed many R packages over his career, notably gam, glmnet,
adelie, lars, uniLasso, svmpath and softImpute, among others.
Heungsun Hwang
Dr. Heungsun Hwang is a Professor of Psychology at McGill University, where he earned his Ph.D. in Quantitative Psychology. His research focuses on the development and application of advanced quantitative methods for measuring and analyzing human characteristics, behaviour, and psychological processes. He is currently integrating statistics, psychology, and machine learning to leverage multifaceted data, including psychological, physiological, neuroimaging, and genetic information, to improve the understanding and prediction of behavioural and cognitive differences. He has served on the editorial boards of several journals, including Psychometrika, Psychological Science, Behaviormetrika, and the British Journal of Mathematical and Statistical Psychology. Lab website: https://sites.google.com/view/hwanglab/
Ndèye Niang
Ndèye Niang is Professor of Statistics and a researcher in data analysis at the CEDRIC laboratory of CNAM Paris. She holds a PhD in Statistics from the University of Paris IX Dauphine, with a thesis on multidimensional methods for statistical process control. Her research focuses on data analysis, data mining, and big data analytics, with particular attention to complex data, including qualitative, mixed, high-dimensional, multi-block, and incomplete data. She has worked on correspondence analysis, discrimination methods, feature clustering, subspace clustering, clusterwise regression, and supervised and unsupervised methods for structured data. Through several MSc and PhD supervisions, she has collaborated with companies and research centres on applications in areas such as the automotive industry, indoor air quality, customer feedback management, and drug side effects. She is the author or co-author of several publications.
Mikael Börjesson
Mikael Börjesson is Professor in Sociology of Education at Uppsala University, Sweden. Börjesson’s research areas are fields of education, the modern history of higher education, elites and elite education, transnational educational strategies and the internationalisation of higher education, social spaces and educational strategies and lifestyles of social groups. He has made extensive use of Geometric Data Analysis in understanding educational fields and social spaces, their structures and transformations.
Börjesson is Scientific leader of the Research Unit Sociology of Education and Culture (SEC) and of The Swedish Centre for Studies of the Internationalisation of Higher Education (SIHE), as well as a member of the steering group for Higher Education and Research as a Field of Study (HERO). Since 2026, Börjesson is teacher representative on the Board of Uppsala University.