European Conference on Data Analysis

9. September 2026 - 11. September 2026

Programm - Programme
 

The programme is still under development.

The Team and Contributors
Local Organizing Commitee
Scientific Commitee
Keynote Speakers - still open!

Practial Informations

Conference Venue
Hotels

About the Conference & City

About Stralsund
Important Dates

The next European Conference on Data Analysis (ECDA2026) will take place from September 9th to 11th, 2026 at Stralsund University of Applied Sciences, Germany. 

We look forward to welcoming you to in Stralsund in 2026!


ECDA is an international conference dedicated to analytical aspects of data science. It connects statistics, computer science, and practical application domains related to all aspects of data analysis. 

The ECDA is organized under the auspices of the 

  • Gesellschaft für Klassifikation - Data Science Society (GfKl).

It will be organzied in cooperation with the:

  • European Association for Data Science (EuADS),
  • Dutch/Flemish Classification Society (VOC),
  • Classification and Data Analysis Group of the Italian Statistical Society (CLADAG),
  • Classification and Data Analysis Section of the Polish Statistical Association (SKAD) and the
  • British Data Science Society (BDSS)

The conference covers methodological topics from the fields of Statistics and Machine Learning such as:

  • Algorithmic fairness,
  • Bayesian methods,
  • Causal inference,
  • Clustering,
  • Computational statistics,
  • Computer vision,
  • Consumer Preferences,
  • Data visualization,
  • Depth-based methods,
  • Explanianble AI,
  • Image analysis,
  • Invariant coordinate selection,
  • Large language models,
  • Meta-analysis,
  • Missing data analysis,
  • Mixture models,
  • Multivariate statistics,
  • Neural networks and deep learning,
  • Partial least squares and structural equation modeling,
  • Preference-based learning,
  • Robust methods,
  • Statistical learning,
  • Symbolic and fuzzy data analysis,
  • Text mining,
  • Tree-based methods,
  • Uncertainty in machine learning

as well as applied Data Science in different domains such as:

 

  • Audio signal analysis,
  • Behavioral data science,
  • Credit scoring,
  • Decision making,
  • Demography,
  • Economics,
  • Epidemiology,
  • Finance,
  • Healthcare,
  • Data Science in HR,
  • Journalism,
  • Marketing,
  • Medicine,
  • Official Statistics,
  • Psychometrics,
  • Risk management,
  • Sensometrics,
  • Social sciences,
  • Tourism

Contact

Prof. Dr. rer. nat.
Gero Szepannek

Statistik, Wirtschaftsmathematik und Machine Learning

Tel:

+49 3831 45 6672

Raum:

322, Haus 21


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