Mathematics and Data Sciences

Digitalization is continuously penetrating our society. Data is increasingly being collected and is omnipresent. It is time to use this data to optimize processes and products.

The mission of the “Mathematics and Data Science” working group is to advance research in the field of machine learning based on data from industrial, economic or physical sources. Our goal is the development of new methods in machine learning and their application in industry and business. Our research includes theoretical and empirical analysis of algorithms, their implementation and adaptation to specific applications and data sets.

Our focus is particularly on the following areas

- Probabilistic machine learning: dealing with uncertainties in data.

- Generative models: modeling real-world data.

- Anomaly detection: Identification of deviations in technical processes.

- Analysis and prediction of industrial time series: Investigation and prediction of trends and patterns in industrial data.

- Processing high-dimensional sensor data: Efficient use and analysis of extensive sensor data.

- Integrating prior physical knowledge into data analysis: Using physical laws and models to improve data analysis.

If you are interested in our research, are considering joint research projects in the field of data analysis and machine learning or would like to write a student thesis, please contact us.