Invited and Contributed Sessions

President’s Invited Session

Berthold Lausen, Theodore Chadjipadelis Data Science Education

Presidential Address

Berthold Lausen Predictive Ensemble Methods for Event Time Data

Invited Sessions

Invited sessions on the following topics have been arranged:

Theofanis Exadaktylos, Theodore Chadjipadelis (GSDA/ECPR) Analysis of European Parliament Elections

José Fernando Vera & Eva Boj del Val (SEIO-AMyC) New developments in clustering and scaling data
Christian Hennig (BCS) Philosophy relevant to classification and data science
Christian Hennig (IFCS Cluster Benchmarking Task Force) Neutral Benchmarking Studies of Clustering
David Hunter (BCS) Statistical theory of cluster analysis
Krzysztof Jajuga (SKAD) Data Analysis in finance
Salvatore Ingrassia (CLADAG) Advances in Mixture Modeling
Nataša Kejžar, Simona Korenjak-Černe, Andrej Srakar (SSS) Advances in classification analysis for complex data – compositional and symbolic approaches
Koji Kurihara (JCS) Clustering for spatio-temporal data and its visualization
Paul McNicholas (CS) Clustering, Classification and Data Analysis via Mixture Models
Angela Montanari (CLADAG) Supervised classification with imprecise labels and complex data
Iannis Papadimitriou (GSDA) Developments of Data Analysis (Analyse des données) in Greece
Jozef Pociecha (SKAD) Classification methods in economics and business
Mark de Rooij (VOC) Crossroads of Statistical Learning and Psychometrics
Niel le Roux (SASA-MDAG) Classification, visualisation and dimension reduction
Thanos Thanopoulos (GSDA/HSA) Official Statistics
Cristina Tortora (GSDA) Clustering categorical and mixed-type data
Aglaia Kalamatianou (Panteion University, Athens) Data mining techniques and classification methods in Social Sciences
Theophilos Papadimitriou, Periklis Gogas (GSDA) Emerging Methodologies in Economics and Finance

Contributed papers from scholars and practitioners are invited on any of the topics below as well as on related issues:

History/Philosophy, Methodological Advances in Clustering and Classification, Exploratory Data Analysis and Data Visualization, Official Statistics, Data Analysis in Economics and Business, Symbolic and Complex Data Analysis, Data Analysis in Biological and Medical Sciences, Statistical Modeling of Psychological Processes, Statistics and Data Analysis in the Social Sciences, Data Analysis in Education and Learning Analytics, Analysis of Network Data / Social Networks