Hi I'm
Mike Coffey

My main areas of research interest lie in the genetic and genomic improvement of farmed livestock for traits valuable to the animal, the farmer and society. This
started in dairy but has expanded to include beef, sheep, goats and pigs. This process is compute intensive and so another area of interest is in the programming and hardware requirements to undertake these analyses more efficiently including hardware and software acceleration using FPGA and GPU devices.

Recently, we have begun exploring the use of Deep Learning to predict new phenotypes from milk mid infra-red spectral data. Successes so far include predicting pregnancy status and bTB status and we are expanding our traits of interest to include Johnes, BVD and contaminants in milk. We will extend our application into analysing CT scan images to extract new phenotypes automatically.

Plant and animal breeding have historically been separate endeavours but more recently we have become interested in the idea of selecting plants and animals
together to maximise efficiency of producing food from natural capital but also
minimising GHG emissions from the entire system.

The recent establishment of the Challenge Centre for Data and Digital Innovation
will create a focus to extend our interest in data into the whole of SRUC. We will
increasingly focus our attention on delivering new solutions from animal and plant
data collected automatically and in great volume.