University
Clermont-Ferrand, FranceThe Uncertainty Quantification (QI - Quantification des Incertitudes) team is a specialized research group within the M3G Department (Mechanics, Mechanical Engineering, Civil Engineering, Industrial Engineering) at the Institut Pascal (UMR 6602) in Clermont-Ferrand, France.
The team’s work centers on ensuring structural safety and performance despite the inherent randomness in materials, manufacturing, and environments. Key research areas include:
-Stochastic Modeling & Statistical Inference: Developing probabilistic descriptions of system inputs and measurement errors.
- Uncertainty Propagation: Using methods like Monte-Carlo simulations and metamodeling (e.g., Kriging, Gaussian Processes) to see how input variations affect system outputs.
- Reliability Analysis: Evaluating the probability of failure for complex structures under static or dynamic loading.
- Optimization under Uncertainty (RBDO): Designing systems that are both efficient and robust against variability.
- AI & Machine Learning Integration: Leveraging Deep Learning and Physics-Informed Neural Networks (PINN) to accelerate simulations and improve predictive accuracy.
Information Science and Engineering (ENG)
Project cooperation
Hybrid Approaches for Deep Learning-Based Structural Health Monitoring
Developing a hybrid bridge monitoring framework integrating physical structural models with deep learning for improved safety assessments.
Assistant professor at Institut Pascal - M3G - Uncertainty Quantification
Clermont-Ferrand, France