Our group designs algorithms and software architectures for inference: converting raw data into semantic understanding that be used for science or engineering. We develop, characterise and apply our algorithms in a variety of domains, from engineering and science through to the so called “digital economy”.

Our inspiration is biology, in two ways. First, the group has always been fascinated by the parallels between biological computation and algorithms that are designed to analyse or draw inference from data. Secondly, however, we have increasingly vast sources of data available to us in the biological sciences: being able to reproducibly analyse such data presents us with a number of challenges.

In some ways, what we do might be characterised, today, as a combination of machine learning and data science. But our biological inspiration is a rather unique flavour. To find out more, drop us a line.