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TU Berlin

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Research Areas

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


  • 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

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