Research Areas

The group contributes to the theoretically well-founded development of novel data analysis techniques, and to their implementation and application. For example:

Algorithms

• Machine learning methods for robust classification and regression of high-dimensional, multivariate data, in particular using support vector machines (SVMs), and artificial neural nets.
• Clustering methods and algorithms for outlier detection.
• Signal processing methods, in particular for the analyis of non-linear and non-stationary time series.

• EEG-based Brain-Computer Interface (BCI)
• Mental workload-detection of car drivers
• Handwritten character recognition (OCR)
• Intrusion detection in computer networks
• Classification of data coming from high-energy physics
• Analysis of DNA and protein structure
• Analysis of finanical data
• Acoustic source separation (cocktail-party problem)
• Computational chemistry