Uncertainty quantification is an academic field and methodological approach focused on identifying, characterizing, and propagating uncertainties in computational and mathematical models and their associated data. It encompasses a suite of techniques to assess how variability and lack of knowledge in inputs affect model outputs and predictions, thereby providing measures of confidence and enabling informed decision-making under conditions of uncertainty.