Uncertainty quantification (UQ) is concerned with including and characterising uncertainties in mathematical models. Major steps include the proper description of system uncertainties, analysis and efficient quantification of uncertainties in predictions and design problems, and statistical inference on uncertain parameters starting from available measurements. Research in UQ addresses fundamental mathematical and statistical challenges, but has also wide applicability in areas such as engineering, environmental, physical and biological applications. This workshop focussed on mathematical challenges at the interface of applied mathematics, probability and statistics, numerical analysis, scientific computing and application domains such as machine learning, modelling of energy production, and bifurcations in climate models. The workshop brought together experts from those disciplines to enhance their interaction, to exchange ideas and to develop new, powerful methods for UQ.