Michael Beigl

Professor, KIT / SDIL

Michael Beigl is professor for Pervasive Computing Systems at the Karlsruhe Institute of Technology (KIT) and head of the TECO research lab. He obtained both his M.Sc. and Ph.D at the University of Karlsruhe (now KIT). Previously he was professor at the TU Braunschweig from 2006-2010, visiting associate professor at Hide Tokuda Labs, Keio University, Japan in 2005 and research director of the TECO, University of Karlsruhe, Germany from 2001-2005. He is heading the national competence center for Big Data AI, the Smart Data Innovation Lab (SDIL) and the state competence center for Big Data AI in Baden-Württemberg, the Smart Data Solution Center (SDSC-BW) since 2014. His research interests evolve around systems for Artificial Intelligence.

Michael is speaking at

Focus Track 3 - Market uptake: Bringing AI and Data Sciences to Practice
November 4, 2020
10:00 am - 11:30 am


  • Daniel Alonso Roman (Chair) ITI - Artificial Intelligence & Big Data Partnerships Driver, BDVA i-Spaces group chair / EUHubs4Data coordinator
  • Guido Reimann (Chair) Expert Software and Digitalization and Coordinator Artificial Intelligence Competence Network of VDMA, VDMA e.V.
  • Michael Beigl (Speaker) Professor, KIT / SDIL
  • Elena Simperl (Speaker) Professor of computer science, King's College London
  • Maria Christina Bienek (Speaker) General Manager, Smart Electronic Factory e.V.
  • Sandro D’Elia (Speaker) Programme Officer - Unit A2: Technology and Systems for Digitalising Industry, European Commission - Directorate General for Communications Networks, Contents and Technology
  • Philippe CALVEZ (Speaker) Head of ENGIE LAB CSAI, Platoon
  • Charlotte Andersdotter (Speaker) Head of Brussels Office, RISE
  • Stelian BRAD (Speaker) Full Professor in Intelligent Robotics and Innovation, Technical University of Cluj-Napoca
  • Javier Valero (Speaker) Digital Innovation Hubs Advisor - "AIR4S" DIH Manager, Universidad Politécnica de Madrid, UPM


The main objective of this track is to make accessible by European industry and society the last advances and tools in Europe on Big Data and AI, to foster the adoption of these tools and services, and to facilitate their market uptake. To accomplish this goal, needs, challenges and barriers from both the offer and the demand side have to be considered. Besides, the successful achievement of this objective implies that we consider simultaneously the European dimension (solutions available at European level) combined with a national and regional perspective (solutions adapted and accessible by local ecosystems). It includes:
  • To understand needs of industry and society both at European and national / regional level
  • To bring to them last advances in Europe on Big Data and AI
  • To make those solutions accessible at regional / local level
  • To support them in the adoption and use of the solutions
  • To find ways of collaboration and understanding of offer and demand sides

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