Research Areas

Artificial Intelligence

„Bringing artificial intelligence into the engineering domains”

With CONTACT Research, we want to bring artificial intelligence (AI) to the engineering domains. The focus of our research is on use cases from the entire product lifecycle. This puts a wide range of technologies, methods, and processes at the center of our work.

  • Natural Language Processing
    Techniques and methods for machine processing of natural language and text.
  • Geometric Deep Learning
    Deep Learning methods that process 3D geometries, classify 3D bodies, and recognize similarities between them.
  • Graph Neural Networks
    Some data structures, such as those of social networks, can be represented as a graph. Graph Neural Networks describe Deep Learning on these graphs.
  • ModelOps and PLM
    Techniques for the implementation of AI projects and their productization.
  • Further methods from the field of Data Science with relevance for specific tasks from PLM and IoT.

Together with our partners from science and industry, we identify relevant data sources and evaluate their quality, assess AI models, and further develop them so that they can be applied to engineering-relevant problems. This is how we make AI-supported functionalities available to industrial business applications.  


A Holistic System Lifecycle Engineering Approach – Closing the Loop between System Architecture and Digital Twins

Gutiérrez-Basulto, V.; Jung, J. C.; Sabellek, L. (2018). Reverse Engineering Queries in Ontology-Enriched Systems: The Case of Expressive Horn Description Logic Ontologies. International Joint Conference on Artificial Intelligence 2018: 1847-1853.


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