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.

Ute Schmid

Volker Tresp

Members of the Working Group

Prof. Dr. Ulf Brefeld
Leuphana University Lüneburg

Dr. Aljoscha Burchardt
German Research Center for Artificial Intelligence (DFKI)

Dr. Carl-Helmut Coulon
INVITE GmbH

Prof. Dr. Wolfgang Ecker
Infineon Technologies AG

Dr. Tim Gutheit
Infineon Technologies AG

Dr. Johannes Hoffart
SAP SE

Prof. Dr. Kristian Kersting
Technical University (TU) of Darmstadt

Prof. Dr. Stefan Kramer
Johannes Gutenberg University Mainz

Prof. Dr. Gitta Kutyniok
Ludwig-Maximilians-Universität München

Prof. Dr. Marius Lindauer
Leibniz University Hannover, L3S Research Center

Prof. Dr.-Ing. Alexander Löser
Berliner Hochschule für Technik

Prof. Dr. Ulrike von Luxburg
University of Tübingen

Prof. Dr. Volker Markl
Technische Universität Berlin

Prof. Dr. Katharina Morik
TU Dortmund University

Prof. Dr. Klaus-Robert Müller
Technische Universität Berlin

Prof. Dr. Wojciech Samek
Technische Universität Berlin, Heinrich Hertz Institute

Prof. Dr. Kai-Uwe Sattler
Ilmenau University of Technology

Philipp Schlunder
daibe UG

Dr. Harald Schöning
Software AG

Dr. Joachim Tödter
KION Group

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

A comprehensive overview of all results and contributions of the working group available in German can be found here.

Publications
Expertise
Videos (German)