IDESSAI 2023: 3rd Inria-DFKI European Summer School on AI

IDESSAI 2023 that will be held from 4 to 8 September 2023 is the third yearly Summer School organized by the two renowned German and French AI institutes, DFKI and Inria, in coordination with 3IA Côte d’Azur. The program features a line-up of courses focused on two themes, Simulation & AI and AI for Agriculture & the Environment, which are at the forefront of socio-economic issues related to AI.

On top of the latest methodological advances and the shared vision of the future that both organizing institutes have to offer, IDESSAI 2023 will be practically oriented. This will be achieved through hands-on courses and the involvement of industry practitioners and innovators.

Participants will be offered the opportunity to present their work to each other in dedicated poster/demo sessions.

Courses for each theme will take place in two parallel tracks. There will be plenty of opportunities to exchange between these two tracks at coffee breaks, meals and social events, as well as through joint cross-track sessions.

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Target Audiences

IDESSAI 2023 was designed for PhD students in all areas of AI, including machine learning, knowledge representation and reasoning, search and optimisation, planning and scheduling, multi-agent systems, natural language processing, robotics, computer vision, and other areas. PhD students in other fields, MSc students, postdocs, and researchers in academia and industry are also welcome.

Venue & Registration

IDESSAI 2023 is planned as a fully in-person event, which will take place at the Inria center at Université Côte d’Azur. Remote attendance will not be possible.

For more details and to pre-register, see https://idessai.eu/registration-2023/ (deadline: June 18, 2023).

Organisers

Co-organized by Inria and DFKI, in coordination with 3IA Côte d’Azur.

Organising Team
Contact: idessai-support@dfki.de.

IDESSAI 2023 stands out from the crowd of offerings for AI students in several aspects:

  • We ensure a good balance in the number of participants and instructors: participants will have the opportunity to join a community of like-minded people and, at the same time, they will be in close contact with the experts.
  • Our program features a line-up of courses focused on two themes, Simulation & AI and AI for Agriculture & the Environment, which are at the forefront of socio-economic issues related to AI.
  • On top of the latest methodological advances and the shared vision of the future that both organizing institutes have to offer, IDESSAI 2023 will be practically oriented. We will achieve this through hands-on courses and the involvement of industry practitioners and innovators.
  • Participants will be offered the opportunity to present their work to each other in dedicated poster/demo sessions.
  • Courses for each theme will take place in two parallel tracks. There will be plenty of opportunities to exchange between these two tracks at coffee breaks, meals and social events, as well as through joint cross-track sessions.

Confirmed Speakers

Cross-track keynotes

  • Stefania Fresca (Politecnico di Milano) – Deep learning-based reduced order models for scientific applications.
  • Siddhartha Mishra (ETHZ) – Learning Operators
  • Bertrand Le Saux (ESA) – Next-Generation Machine Learning for Earth Observation.
  • Roland Lenain (INRAE) – Robotics for agriculture.

Simulation & AI Track

  • Victor Michel-Dansac (Inria) – Numerical schemes for hyperbolic equations enhanced by Scientific Machine Learning.
  • Régis Duvigneau (Inria) – Physics-informed neural networks for simulation.
  • Guillaume Cordonnier (Inria) – Deep learning for fast and efficient glacier modeling, with applications in glacial erosion.
  • Matthieu Lecce (AI Verse) – Generating synthetic datasets for computer vision applications
  • Shai Machnes (Qruise) – Qruise: First steps on the path to an ML Physicist.
  • Mathieu Desbrun (Inria and Ecole Polytechnique) – Super-resolution via AI for fluid simulation.Gaétan Bahl (NXP Semiconductors) – Applications of AI inference at the edge with NXP processors.

AI for Agriculture and the Environment Track

  • Odalric-Ambrym Maillard (Inria) – Reinforcement learning and application to sustainable gardening.
  • Alexis Joly (Inria) – Cooperative learning for biodiversity monitoring: how does the Pl@ntNet platform work and how can you use it in your own application?
  • Diego Marcos (Inria) & Dino Ienco (INRAe) – AI for Earth surface monitoring through satellite image time series data.
  • Olivier Bernard (Inria) – Hybrid modelling of artificial microbial ecosystems for bioenergy production and wastewater treatment.
  • Matthias Nachtmann (BASF) – The beauty of data – the core ingredient for scalable, sustainable crop production.