Data Science & AI

The data volume generated in laboratory and process analytics are continuously and rapidly growing due to increasing sensor resolution, multimodal measurement principles, parallelization and laboratory automation. An end to this development is not foreseeable. On the contrary, due to the increasing real-time connectivity of laboratory and process data sources in the context of the Internet-of-Things (IoT) principle, an increasing number of value-added approaches are becoming conceivable using model-based simultaneous evaluation of multiple analytical methods.

In this context, CHARISMA conducts research with large and diverse data sets generated in instrumental analytics (such as ion mobility spectroscopy, IMS), process analytics (such as ATR-FTIR, NIR spectroscopy, and online MS), surface analysis, and material research.

This includes methods of tailored data management, such as the selection of adequate SQL or NoSQL technologies for data ingestion and storage, as well as data pre-processing and data cleansing. Furthermore, the evaluation with knowledge-based and statistical models (scientific modeling / machine learning) as well as their scalable implementation in contemporary technology stacks is developed. The final goal is the deployment of our models using cloud-based apps ("model as a service") and the resulting seamless integration into automated analysis processes.

Prof. Dr. Simeon Sauer

Building G, Room 225

+49 621 292-6385
Email

Faculty of Biotechnology

 

Prof. Dr. Oliver Hummel

Building A, Room 007a

+49 621 292-6223
E-Mail

Fakultät für Informatik