Statistical Machine Learning for Engineering with Applications

Jürgen Franke has been a professor of Applied Mathematical Statistics and the speaker of the interdisciplinary Center for Mathematical and Computational Modelling (CM)² at the University of Kaiserslautern. Since his retirement from teaching, he joined the Fraunhofer Institute for Industrial Mathematics (ITWM) as a scientific consultant on statistics. His research focuses on nonlinear time series analysis, nonparametric statistics and statistical learning with applications in engineering and finance.

Anita Schöbel is professor of Applied Mathematics at the University Kaiserslautern-Landau and head of the Fraunhofer Institute for Industrial Mathematics (ITWM). Currently she is also president of the Association of European Operational Research Societies (EURO). At Fraunhofer Society she is responsible for the strategic research area Next Generation Computing and vice spokesperson for the quantum computing competence network. Her research focuses on discrete optimization and on robust and multi-objective optimization with applications in transportation.

- An Introduction of Statistical Learning for Engineers.- Machine Learning for Inline Surface Inspection Systems - Challenges, Approaches, and Application Example.- Gaussian Process Regression for the Prediction of Cable Bundle Characteristics.- Machine Learning for Predictive Maintenance in Production Environments.- Detecting Healthcare Fraud Using Hybrid Machine Learning for Document Digitization.- Cracks in concrete.- Machine learning methods for prediction of breakthrough curves in reactive porous media.- Segmentation and Aggregation in Text Classification.- Hardware-aware Neural Architecture Search.- Optimal Experimental Design Supported by Machine Learning Regression Models.- Data Analytics, Artificial Intelligence and Machine Learning in Mobility and Vehicle Engineering.