Skip to main content Skip to navigation


Methodological Themes

The Centre focuses on a number of fundamental themes common to many scientific applications, including:

  1. Mathematical and Statistical Foundations
  2. Physics-based UQ and predictive modelling (aligned with the Alan Turing Institute's data-centric engineering programme)

Application Themes

Application themes at WCPM are:

  1. Electronic Devices (Energy GRP)
  2. Environmental Sustainability (Sustainable Cities GRP, Food GRP)
  3. Biochemical/biomedical systems (Health GRP)

Objectives of WCPM

WCPM is an inderdisciplinary centre addressing the mathematical, statistical and scientific computing challenges necessary for predictice modelling in science and engineering. Our fundamental approach is in exploring synergies between Uncertainty Quantification (UQ), Machine Learning (ML) and Scientific Computing. The broad objectives of the Centre are:

1 To develop rigorous mathematical theory, algorithms and software to enable the quantification, analysis and subsequent control of complex multiscale systems in the presence of uncertainties, in a computationally scalable way
2 To demonstate how a mathematical framework that addresses stochastic multiscale systems can be driven by limited and gappy information, leading to a completely new approach to capture and exploit uncertainty in engineered systems
3 To demonstrate the physical relevance and broad applicability of our multiscale framework through the consideration of a number of application themes

The emphasis of the Centre is on common themes linking the UQ, ML and Scientific Computing communities and identifying innovative research directions that can accelerate the impact of uncertainty modeling in engineering and the sciences as well as demonstrate the capabilities of computational uncertainty quantification methods and tools in various problems.