Prof. Dr. Björn Eskofier
image: FAU/K. Fuchs

Prof. Dr. Björn Eskofier

Chair of Machine Learning and Data Analytics

AI in Medicine

  • Engineering integration of ML/AI technologies in sports and medical technology (e.g. calculation of biomechanical parameters for objective diagnostics)
  • Holistic intelligent medical technology through the composition of ML/AI algorithms and embedded/ubiquitous computing systems (e.g. ambulatory gait analysis for Parkinson’s patients, fall detection)
  • Medical ML/AI applications from the perspective of human-computer interaction research (e.g. acceptance and usability of ML/AI assistance systems in everyday clinical practice)

Basic Research

  • Seamless coupling of ML/AI algorithms (e.g. feature selection and classification)
  • Resource-efficient classification (e.g. SVMs)
  • Balancing between model quality and resource requirements
  • Unbiased evaluation of ML/AI models for multi-class problems