Hybrid: SIAM Conference on Uncertainty Quantification (UQ22)

Uncertainty quantification (UQ) is essential for establishing the predictive accuracy of computational models for essentially all fields of science and engineering. The recent pandemic has highlighted the importance of quantifying uncertainty when working with potentially inaccurate models and insufficient data. UQ is an inherently interdisciplinary field based on a broad range of mathematical and statistical foundational topics and associated algorithmic and computational developments. UQ22 will bring together mathematicians, statisticians, scientists, and engineers interested in the theory, development, and implementation of UQ methods. Whereas a broad range of topics will be represented, major conference themes will include mathematical and statistical foundations of UQ, model-informed and data-driven UQ approaches, and applications of UQ in the biological, medical, climate, and physical sciences. The goal of the conference is to provide a forum for exchanging ideas between diverse groups from academia, industry, and government laboratories, thereby enhancing communication and contributing to future advances in the field.