15–16 May 2024
Europe/Berlin timezone

Welcome to the ENBIS Spring Meeting 

Trustworthy Industrial Data Science

Dortmund, Germany, May 15-16, 2024

Copyright: Fachhochschule Dortmund / Roland Baege

Aim of the Spring Meeting

Advanced statistical and machine learning models as well as adaptive and intelligent methods are becoming increasingly important in applied data science. At the same time, their trustworthiness is critical for the progress and adoption of data science applications in various fields, especially in industry. This ranges from methods to improve data quality, explainability, robustness and fairness to mathematical reliability guarantees. To discuss these within our ENBIS, the 2024 Spring Meeting brings together both academic and industrial statisticians interested in theoretical developments and practical applications in trustworthy data science.

Topics include but are not limited to:

  • Empirical Studies on Trustworthy Data Analytics
  • Explainable Artificial Intelligence in Medicine
  • Fairness of Predictive Models
  • Global Sensitivity Analysis
  • Interpretable Machine Learning
  • Methods to increase Data Quality
  • Statistical Learning for Industry
  • Statistical Reliability and Robustness
  • Trust in Intelligent Systems and Methods
  • Trustworthy Design and Analysis of Computer Experiments
  • Trustworthy Anomaly Detection


Contact information

For any question about the meeting venue and scientific programme, registration and paper submission, feel free to contact the ENBIS Permanent Office : office@enbis.org.

Organizing Committee:

Sonja Kuhnt (Chair), Dortmund University of Applied Sciences and Arts, Germany

Nadja Bauer, Dortmund University of Applied Sciences and Arts, Germany

Ulrike Guba, TU Dortmund University, Germany

Markus Pauly, TU Dortmund University, Germany


Programme committee

Nadja Bauer, Dortmund University of Applied Sciences and Arts, Germany

Christoph Friedrich, Dortmund University of Applied Sciences and Arts, Germany

Bertrand Ioos, EDF R&D, France

Sven Knoth, Helmut Schmidt University Hamburg, Germany

Sonja Kuhnt, Dortmund University of Applied Sciences and Arts, Germany

Antonio Lepore, University of Naples Federico II, Italy

Markus Pauly, TU Dortmund University, Germany

Olivier Roustant, INSA Toulouse, France

Heike Trautmann, Paderborn University, Germany


ENBIS Spring Meeting 2024 Highlights

Plenary speakers

Nicolas Brunel (ENSIIE, France): Statistical Inference for Trustworthy AI: Cases for xAI and Uncertainty Quantification

Jean-Michel Loubes (Université Toulouse Paul Sabatier, France): Towards Compliance of AI Algorithms : Bias Analysis and Robustness

Muhammad Bilal Zafar (Ruhr University Bochum, Germany): On Trustworthiness of Large Language Models

The meeting will also include a number of contributed sessions. A particular focus will be given on Trustworthy Industrial Data Science. For the conference, you can submit either an oral or poster/blitz presentation.

A special issue of the Wiley Journal Applied Stochastic Models in Business and Industry will be published on the topics of the meeting.


Emil-Figge-Straße 42, 44227 Dortmund
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