Uncertainty Quantification Lab’s mission is to accelerate discoveries and decision-making under uncertainty through novel computational tools based on a deep integration of computation, modeling, and experimentation.
What is UQ?
Uncertainty Quantification (UQ) is the theoretical and computational fabric that connects the three pillars of science – theory, experimentation, and computation – through which uncertainties are characterized and informed to guide the scientific discovery and decision-making process.
The central challenge in using computational models for scientific discovery, engineering design, or decision support is that the process follows a path contaminated with errors and uncertainties. The inherent uncertainties are the result of many factors: experimental uncertainties, model structure inadequacies, uncertainties in model parameters and initial conditions, as well as errors due to sampling and numerical discretization.
The UQ research activities in our group fall into two categories: development of methodologies and algorithms and applications via funded collaborations with researchers in various sciences and engineering disciplines. Every project is a mixture between methodology development and application, and as such, every graduate student in the UQ lab is exposed to both methodology and application.