ACEMS Research

Challenging data

Modern data comes in all sorts of different forms that do not necessarily fit well with traditional data analysis methods. For example, it can occur in the form of images, text, visual displays or mathematical functions. The size of datasets can be much larger than those traditionally analysed and the speed at which decisions have to be made about such data can be much faster than previously required. Under this theme we explore these data sources different types of challenging data and develop new methods to explore such data for its analysis.

Multiscale models

Models are the fundamental structures required to make sense of data and systems. Under this theme we develop the new models, both stochastic and statistical in nature, required by new problems and to support Challenging Data.

Enabling Algorithms

Developments in computing technology have provided the opportunity for the creation of new algorithms to enable improved analysis of data and models. Under this theme we develop the new enabling algorithms required for Challenging Data, the new Multiscale Models and other advances.

Informed Decisions

The purpose of data collection and modelling is to learn more about the system and make the best possible decisions about it. Under this theme we develop new decision-making methodologies, and exploit Challenging Data, Multiscale Models, and Enabling Algorithms to make decisions.

ACEMS Publications

Publications from our researchers

Green Acorn