Uncertainty quantification for complex systems: theory and methodologies

In areas as diverse as climate modelling, manufacturing, energy, life sciences, finance, geosciences and medicine, mathematical models and their discretisations into computer models are routinely used to inform decisions, assess risk and formulate policies. How accurate are the predictions made using such models? This crucial question lies at the heart of uncertainty quantification (UQ).UQ is a broad phrase used to describe methodologies for taking account of uncertainties when mathematical and computer models are used to describe real-world phenomena. This includes propagating uncertainty from unknown model inputs to model outputs, the study of uncertainty in the models themselves, developing approximation schemes that result in tractable and accurate computer models, robust design, model calibration and other inverse problems, model bias and discrepancy etc. This programme focuses on UQ for complex systems which have complicated mathematical descriptions such as systems of partial