CITCoM

What is CITCoM and what is it aiming to achieve?

CITCoM is a 3.5 year research project funded by the EPSRC, running from early 2021 until mid 2024.

Computational models are becoming increasingly pervasive and important. This was illustrated in recent months, where government responses to the COVID pandemic have been largely informed by computational models. Clearly, it is important that these models are "correct" - incorrect outputs could potentially have disastrous consequences.

Computational models are commonly written in conventional programming languages, but are often harder to test than conventional systems for various reasons. For example, they tend to require large numbers of parameters, can take a long time to execute, and are often exploratory in nature, making it difficult to discern whether an output is to be expected or not.

To work around these problems, CITCoM will investigate the application of a family of statistical analysis approaches known as Causal Inference. These approaches provide a framework within which to select suitable parameter configurations, and to draw justifiable conclusions about model behaviour from small samples of executions (or simulations). There is even the possibility for counterfactual reasoning - answering "what-if" questions about executions that have not yet been executed.

CITCoM will use these capabilities to develop powerful new tools and methodologies, which can be used by modelling practitioners to rigorously test their computational models.