Data Science

This research project focuses on the methodological and application aspects of how to explain what a deep neural network learns through training. Specifically, this project tackles the development of methods for concept extraction, localization, and learning, as well as their applications in industrial scenarios.

The vision of the IoP was to enable a new level of cross-domain collaboration by providing context-aware data and AI methods from production, development and usage in real-time on an appropriate level of granularity.

The aim of the QUISS project was to develop data-based applications using modern data science and artificial intelligence approaches to optimize or support the scheduling and maintenance of rail vehicles.