Unit, Data Science for Innovation

The research unit “Data Science for Innovation“ develops digital tools for knowledge transfer and thus supports the innovative capacity of industry and research. To this end, the researchers build up an extensive data base and develop intelligent applications based on it using machine learning and network analyses. With their competencies in the field of data science and artificial intelligence, they support other researchers and companies and can contribute significantly to the successful transformation of economic and social structures.

Industry and Research Projects


Connect & Collect: AI-powered cloud for interdisciplinary collaborative research and innovation


Markets for International Technology Transfer - MarketsFITT

Scientific Library on Regional Development

In this scientific infothek, you will find bundled information on how research contributes to successful structural change. We report on scientific models, instruments and procedures for regional development and transformation processes and the resulting policy advice. This page is updated regularly. If you have any comments, please feel free to contact the editors.


Scientific Library on Regional Development

Regional Development and Innovation Policy Division

This research unit belongs to the scientific portfolio of the Regional Development and Innovation Policy Division.


Publication Type
2022 Using vector representations for matching tasks to skills
Amin, Miriam; Bergmann, Jan-Peter; Campbell Borges, Yuri Cassio
Conference Paper
2021 Data-driven identification of idioms in song lyrics
Amin, Miriam; Fankhauser, Peter; Kupietz, Marc; Schneider, Roman
Conference Paper
2021 How to Find New Industry Partners for Public Research: A Classification Approach
Trela, Karl; Campbell, Yuri; Dornbusch, Friedrich; Pohle, Anna
Journal Article
2021 Shallow Context Analysis for German Idiom Detection
Amin, Miriam; Fankhauser, Peter; Kupietz, Marc; Schneider, Roman
2021 Ausgründungen aus der außeruniversitären Forschung: Gründungsdynamik und Erfolgsbedingungen im Ost-West-Vergleich
Kahl, Julian; Dornbusch, Friedrich; Pohle, Anna; Trela, Karl; Weiße, Marlen
2020 Too big to see: Exploring proxies of structure in a real large-scale university-industry cooperation network
Campbell, Yuri
2020 A Survey on Approaches to Computational Humor Generation
Amin, Miriam; Burghardt, M.
Conference Paper
Diese Liste ist ein Auszug aus der Publikationsplattform Fraunhofer-Publica

This list has been generated from the publication platform Fraunhofer-Publica


Research assistants

  • Pier Achkar
  • Anna Rupp
  • Jonas Wolff
  • Marius Zetzsche