School of Mathematical Sciences

Uncertainty Quantification


Mathematical models are imperfect because they are based on our flawed understanding of the world and they often rely on unknown or immeasurable information.

Uncertainty Quantification is concerned with understanding and calculating the uncertainties inherent in such scientific problems. For example, we might use mathematical models that allow us to predict climate change, but the models used can only approximate the real world and so the results from the model will be uncertain.

Researchers at the University of Nottingham are focusing on Uncertainty Quantification to improve our predictions of climate change and its impacts, and assessing the safety of geological disposal of radioactive wastes and carbon capture/storage schemes.

Example projects include:

  • ABC methods for calibrating stochastic simulators
  • Carbon Capture and Storage
  • Diagnosing errors for dynamical systems
  • Engineered barrier for radioactive waste repository
  • Gaussian process emulators for groundwater flow problems
  • GPEs applied to spreading of CO2 plumes in aquifers
  • Multilevel Monte Carlo for groundwater flow and radionuclide transport
  • Multilevel Monte Carlo for groundwater flow and radionuclide transport
  • Numerical methods for SDEs applied to UQ
  • Paleo climate reconstruction
  • Parameter estimation for ODEs and SDEs
  • UQ applied to groundwater flow
  • UQ for performance of air riding seals and bearings
  • UQ in manufacturing composites

Group members

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Professor Ian Dryden

School of Mathematical Sciences

University of Nottingham

University Park



t: +44 (0)115 84 67412 

School of Mathematical Sciences

The University of Nottingham
University Park
Nottingham, NG7 2RD

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