Dr. Patrick Krauß
image: P. Krauss

AI Research Fundamentals

  • Language Processing in Artificial Neural Networks and the Brain
  • Integration of AI and Neuroscience
  • Application of neuroscience methods and development of novel methods for interpreting artificial neural networks (black box problem, explainable AI)
  • Transfer of information processing principles from neurobiology to AI systems (neuroscience inspired AI)
  • Investigation of structural and dynamical properties of recurrent neural networks (RNNs) with methods and concepts from theoretical physics (information theory, dynamical systems and chaos theory, random matrix theory, theory of complex systems, network and graph theory)

AI in Medicine

  • AI as a tool for the analysis and visualization of high-dimensional data from neuroscientific experiments with electroencephalography (EEG), magnetoencephalography (MEG) and invasive cortical recordings
  • AI, especially deep neural networks as a model of brain function