Digital French-German Summerschool on AI for Industry – 24 June 2020

“Innovation, European cooperation and our partnerships are stronger than a virus” have declared the organisers of the annual French-German Summerschool on AI for Industry. This is why a digital event has been conceived to replace the Summerschool initially planned to take place in France with French and German industry players, prominent researchers and French and German policy makers.

The transformed 2020 virtual French-German Summer-school on AI Engineering, AI for the Good, and Machine Learning will therefore take place digitally on 24 June.

In the morning , participants will have the possibility to watch videos sent by other participants, in the afternoon to take part remotely in a live digital plenary session.

Pre-registration via Event-Brite

PROGRAMME – Wednesday 24 June 2020 – 100% online!

Morning        Free watching of short videos on http://mlmda.cmla.fr/videos-of-the-digital-french-german-summer-school-with-industry-2020/from

  • industry partners (on how they relate to the Summer-school’s topics)
  • academia and research (on scientific topics)
  • policy partners (on the French-German cooperation)

Afternoon    Live plenary session (pre-register here!)

13.00 – 13.15    Join in the digital live event (Microsoft Teams)

13.15 – 13.50    Official opening

13. 50 – 14.50    Session 1 – Machine Learning (chaired by Ecole Normale Supérieure Paris-Saclay)

  • Hybrid Models in Product DesignbyFrancois Deheeger, Michelin Lead Data Scientist, France
  • Machine Learning Use Cases at a Transmission System Operator by Fikri Hafid, Réseau de Transport d’Electricité Head of R&D Studies, France
  • Machine Learning Engineerging and Sustainability by Michael Granitzer, Passau University Professor for Data Science, Germany
  • Q&A on the 3 presentations and panel discussion

14.50 – 15.00      Active Break

15.00 – 16.15             Session 2 – AI for the Good (chaired by Siemens)

  • AI for the Good; a Corporate View by Benno Blumoser, Siemens AI Lab Munich, Germany
  • ONADAP – a Visualization and Decision Support Tool for Dynamic Human & Material Resources Allocation within Hospital Facilities in Times of Sanitary Crisis by Brian Tervil, Paris University Researcher, France
  • Data Powered Positive Deviance and Beyond – Using AI for Sustainable International Development by Valentin Kruspel, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), Junior Expert Data for Development & Digitisation, Germany
  • Using Data Analytics and Machine Learning to Control Wildfire by Julia Gottfriedsen, German Aero-Space Center (DLR) Environmental Data Science Researcher, Germany
  • Q&A on the 4 presentations and panel discussion

16.15 – 16.20      Short Break

16.20 – 17.20  Session 3 – AI Engineering (chaired by Passau University)

  • Causality and big data analytics: risks, challenges and solutions by Gianluca Bontempi, Université Libre de Bruxelles Professor and Co-Head at Machine Learning Group, Belgium
  • Self Organising Maps for Anomaly Detection in an Operational Context by Matthias Laporte, Inspector at Banque de France, France
  • Machine Learning and AI in Practice – Insights into use cases from the BMW Group by Tobias Bürger, BMW Lead Big Data and AI Platform, Germany
  • Q&A on the 3 presentations and panel discussion

17.20 – 17.30 Wrap-up and Closing

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