WG 1: Technological Enablers and Data Science

The greatest progress in Artificial Intelligence has been currently made in the field of machine learning. This new knowledge - in combination with extensive data sets and high computing capacity - has become a key economic factor in various areas of science and industry. Data science comprises the entire process of data management: curating, cleansing, analysing and saving data are part of this special procedure. New forms of learning have evolved over the previous years, such as creating and using new knowledge-based systems, analysing given databases (e.g. for recommendation systems), learning from large data streams and using the acquired knowledge in real time.

Topics and Organisation of the Working Group

The working group examines the technological principles and enablers of self-learning systems. It fulfils a cross-sectoral function for the entire platform and provides key impetus to all the other working groups.

Katharina Morik

Volker Markl

Members of the Working Group

  • Prof. Dr. Ulf Brefeld
  • Leuphana University Lüneburg
  • Dr. Carl-Helmut Coulon
  • Dr. Wolfgang Ecker
  • Infineon Technologies AG
  • Prof. Dr. Kristian Kersting
  • Technical University (TU) of Darmstadt
  • Dr. Markus Kohler
  • SAP SE
  • Prof. Dr. Stefan Kramer
  • Johannes Gutenberg University Mainz
  • Prof. Dr.-Ing. Alexander Löser
  • Beuth University of Applied Sciences Berlin
  • Prof. Dr. Klaus-Robert Müller
  • Technische Universität Berlin
  • Prof. Dr. Erhard Rahm
  • Leipzig University
  • Prof. Dr. Wolfgang Rosenstiel
  • University of Tübingen
  • Prof. Dr. Kai-Uwe Sattler
  • Ilmenau University of Technology
  • Dr. Harald Schöning
  • Software AG
  • Prof. Dr. Volker Tresp
  • Ludwig-Maximilians-Universität München
  • Dr. Jilles Vreeken
  • Helmholtz Center for Information Security (CISPA) / Max Planck Institute for Informatics
  • Prof. Dr.-Ing. Gerhard Weikum
  • Max Planck Institute for Informatics
  • Prof. Dr. Stefan Wrobel
  • Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS

We have received written consent from the listed persons for the publication of their data in accordance with the DSGVO. This list of members is an excerpt and will be completed continuously.

Key Questions for the Working Group

  • What are the most important research areas for Artificial Intelligence, Machine Learning and Data Science? Which potential do they hold for disruptive applications?
  • What are the strengths and weaknesses within German AI-research?
  • How can we improve education for researchers and skilled employees for Machine Learning and Data Science?
  • Which research expertise is required for application?
  • How can we accelerate the transfer from successful research to application? Which factors could be obstructive?

Results and Contributions of the Working Group

  • Publications

  • Videos

Stefan Wrobel
Director of the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS assesses, where AI technology will take us (in German).

Kristian Kersting
Professor at the Computer Science Department of the TU Darmstadt University speaks about the new White paper by WG 1 (in German).

Stefan Kramer
Professor at the Institute of Computer Science of Johannes Gutenberg University Mainz, answers the question, how AI systems will affect security and privacy (in German).

Coordination of the Working Group at the Managing Office: Maximilian Hösl