UNCECOMP 2025 is the sixth edition of the International Conference on Uncertainty Quantification in Computational Science and Engineering and one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). UNCECOMP 2025 will be held in conjunction with the 10^th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2025), also an ECCOMAS Thematic Conference.

Conference Topics

The conference topics include (the list is indicative):

• Convergence and error estimation
• Efficient solvers
• Homogenization
• Large-scale stochastic finite element applications
• Markov Chain Monte Carlo methods
• Methods for improving the efficiency of Monte Carlo Simulation
• Microstructure/morphology characterization
• Multiple time scale modeling of nonlinear/chaotic systems, e.g. molecular dynamics
• Multiscale methods involving uncertainties
• Multiscale stochastic dynamics
• Multiscale stochastic finite element methods
• Random field modeling of multiscale systems
• Simulation of random fields
• Solution of stochastic partial differential equations
• Stochastic fracture and damage
• System reliability analysis, design and risk assessment
• Uncertainty quantification
• Upscaling of statistical defects at micro- and nano-scale
• Validation of stochastic modeling techniques
• Wave propagation in micro-structured random media

Minisymposia

Minisymposium 1
« Uncertainty Quantification, reliability, and sensitivity analysis under limited data »

Minisymposium 2
« Physics-Enhanced Machine Learning in Engineering »

Minisymposium 3
« Methodological Developments and Applications of Global Sensitivity Analysis in Science and Engineering »

Minisymposium 4
« Model Reduction for Uncertainty Quantification »

Minisymposium 5
« Uncertainty Propagation and Probabilistic Performance Assessment in Engineering Structures »

Minisymposium 6
« Uncertainty Quantification and Scientific Machine Learning on Manifolds for Reliable Data-driven Modeling and Simulation in Science and Engineering »

Minisymposium 7
« Surrogate models for uncertainty quantification: new trends »

Minisymposium 8
« Uncertainty Quantification in Vibration based Monitoring and Structural Dynamics Simulations »

Minisymposium 9
« Software for Uncertainty Quantification »

Minisymposium 10
« Uncertainty Quantification, Probabilistic and Generative Models in Computational Structural Dynamics »

Minisymposium 11
« Optimal Design of Experiments for Uncertainty Quantification in Computational Models »

Minisymposium 12
« Multiscale and Multiphysics Modelling for ‘Complex Materials “(MMCM 21) »

Minisymposium 13
« Monte Carlo Sampling for Stochastic Solvers: Advances in Uncertainty Quantification »

Minisymposium 14
« Optimization under Uncertainty »

Minisymposium 15
« AI-Enhanced Multiscale and Multiphysics Modeling for Robust Uncertainty Quantification »

Minisymposium 16
« Multi-fidelity information management to mitigate high-fidelity data scarcity in computational science and engineering »

Minisymposium 17
« Bayesian Computation Methods for Inference in Science and Engineering »

Minisymposium 18
« Uncertainty Quantification in the era of Self-Supervised Learning and Neural Operators »

Minisymposium 19
« Uncertainty quantification and Machine Learning Applications in Sciences and Engineering »

Minisymposium 20
« Advancing Scientific Discovery with SciML: Neural Operators, Generative Modeling, and Physics-Informed Techniques »