UQDM 2025

Uncertainty Quantification for Dynamical Modelling
Edinburgh, July 9–11

Workshop Aims

Dynamical modelling is at the core of many disciplines across science and engineering. As the complexity of models grows, so does the scale of the challenge in quantifying relevant uncertainty. Uncertainty arises in models themselves, in their parameters, and in observations. Answering scientific questions in the presence of this uncertainty requires sophisticated tools.

This workshop will cover key topics in the area, such as data assimilation, statistical inverse problems, and surrogate and reduced-order modelling, all in the context of dynamical models. It will draw on expertise across domain boundaries and focus on common challenges, especially the development of accurate and efficient methods for dynamical uncertainty quantification.

The workshop will feature invited and contributed talks as well as a poster session. To participate, please go to our registration page.

Confirmed Invited Speakers

• Eviatar Bach, University of Reading
• Michal Branicki, University of Edinburgh
• Peter Challenor, University of Exeter
• Andrew Curtis, University of Edinburgh
• Svetlana Dubinkina, Vrije Universiteit Amsterdam
• Sebastian Krumscheid, Karlsruhe Institute of Technology
• Abdul-Lateef Haji-Ali, Heriot-Watt University
• James Maddison, University of Edinburgh
• Chris Oates, Newcastle University
• Bojana Rosic, University of Twente
• Katherine Tant, University of Glasgow

Organizers

Martin Brolly, University of Edinburgh
Aretha Teckentrup, University of Edinburgh