DYNAMO Inria Associate Team
DYNamical systems, Analysis, and Machine learning for self-Organization of matter
Inria Associate Team
MALICE (France)
CSML (Italy)
DYNAMO is an Inria Associate Team jointly established between the MALICE Inria project-team at Université Jean Monnet (Saint-Étienne, France) and the Computational Statistics and Machine Learning (CSML) group at the Istituto Italiano di Tecnologia (Genoa, Italy).
It brings together researchers from France and Italy to explore the intersection of machine learning, dynamical systems, and physics-informed modeling.
The team aims to develop new mathematical and computational frameworks to learn and control self-organizing phenomena—complex processes through which matter spontaneously forms ordered patterns under laser excitation. These efforts address fundamental scientific questions while enabling practical advances in surface engineering, with potential applications spanning materials science, energy, health, and nanotechnology.
news
| Nov 01, 2025 | We will be at the EurIPS 2025 workshop SysDiff to present our work on Douglas-Rachford Splitting for Hybrid Differentiable Models. |
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| Sep 18, 2025 | Our paper Conformal Online Learning of Deep Koopman Linear Embeddings has been accepted to NeurIPS 2025! |
| Mar 20, 2025 | Creation of the Inria Associate Team DYNAMO. |