ongoing projects

  • Causality Project

    We model causal relationships with information-theoretic tools. The goal is to automatically retrieve DAG structures representing causality in different application areas.

  • EEG Project

    This project’s goal is to search for biomarkers in EEG recordings in order to help in the diagnosis and risk assessment of neurodegenerative diseases.

  • HIV Project

    This project aims to understand the pathomechanisms of HIV-1 based on interactions between the host and virus using novel machine learning techniques.

  • WeObserve Project

    Many phenomena in our environment are extremely complex and cannot simply be captured via sensors. Additional field observations are often indispensable. This project uses two case studies to examine how sensor data and field observations can be combined and evaluated.

  • MARVEL Project

    The goal of this project is the design and discovery of novel materials as well as their chemical properties by using both traditional machine learning and deep generative models.