Rapid growth in computational resources has heightened the expectation that scientific knowledge can indeed be a driver for societal well-being and betterment. At the same time, our ability to measure the natural and social world around has significantly increased, aided by technological development in sensors, the internet, and other modalities of communication. Science is thus faced, simultaneously, with a complex description of reality at an unprecedented resolution, and the possibility to describe this reality with mathematical models of increasing complexity. Probabilistic formulations of physical problems can be viewed as attempts to adapt rational procedures to this complexity, while tackling the conceptual challenges they inevitably present. As a testament to the significance of this confluence of mathematics, science, and technology, Uncertainty Quantification is arguably one of the fastest growing sub-disciplines in mechanics.
The communities of computational science, stochastic analysis, and statistics have evolved largely along distinct paths. To forge ahead, however, in the direction of transformative scientific impact, requires symbiotic exchange and collaboration. It is the intent of this Workshop on Uncertainty Quantification to bring together leading researchers in these three fields in order to delineate new horizons and forge new synergies that will accelerate the evolution of UQ capabilities to become an enabler of scientific and economic progress.