Objectives of the chair The project has a high degree of continuity with the great success of the 3IA Aniti and DEEL program: studying 1-Lipschitz neural networks, a class of robust by-design neural networks. The team, built in this first round, was composed of Mathematicians, Computer Science researchers, Data-scientists and Industry experts, and has published
Decision-making problems are ubiquitous in industry, from production optimization to in-service product operation management, including internal project and resource optimization. In the last decades, many data-driven (e.g. Deep Reinforcement Learning) and model-based (e.g. AI Planning, Constraint Programming) approaches have been separately investigated to solve those problems. While the former often need a huge amount of
Accurate numerical simulations of river flows, at both territorial and global scales, as well as of marine flooding, have become crucial for modern societies for multiple reasons. Floods—whether inland or coastal—and water flows at the territorial scale result from complex processes that can be described by nonlinear mathematical models based on differential equations. Purely physics-based
Objectives of the chair Embedding of ML model algorithms in safety-critical products, in particular in the aeronautical domain subject to stringent certification, is a significant need of transportation industries. For the past few years, several certification standards have been under development to define the objectives and activities enabling their use in the aeronautical field: –
Objectives of the chair There is an increasing need for efficient methods to approximate values of secure operating conditions for electrical power systems. Indeed, recent and ongoing changes in the European power network, such as the increase in renewable energy sources interfaced by power electronic devices, are bringing up new challenges in terms of power
Recent Earth Observation (EO) systems have opened up new opportunities for land survey systems that provide critical information for climate change monitoring, mitigation, and adaptation. Monitoring Essential Climate and Biodiversity Variables (EVs) provides key information to understand climate, biodiversity and environmental changes. However, retrieving EVs from multi-source data is challenging due to the singularities of