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.