I am a zoologist / experimental psychologist whose research interests primarily concern computational approaches to applied vision and questions lying at the intersection of sensory biology, psychology, history and art. I am particularly passionate about how visual scenes can be “understood” using computer vision and what comparisons can be drawn with biological visual systems. 

Projects I work on:

Automatic disease detection and monitoring in calves

I am an EPSRC Innovation Fellow on a project developing automatic disease detection and monitoring in domestic cattle calves. The project uses artificial intelligence techniques, coupled with visible-range and thermal cameras, to identify Bovine Respiratory Disease (BRD), one of the most common and costly diseases affecting cattle in the world, at the earliest possible stage. My work includes building sensors, deploying and maintaining equipment on farms, establishing efficient data transfer protocols and analysing data using deep neural networks. 

Camouflage Machine

An ongoing research to develop a toolkit and pipeline in order to establish the best (or worst) camouflage for any object in any environment for any viewer using deep neural networks. A paper on establishing optimal colours for concealing and visibility can be found here. 

Modelling the evolution of camouflage using Generative Adversarial Networks

This research, supported by Nvidia, investigates how competing deep neural networks can be used to evolve camouflage patterns. Our team has demonstrated how Generative Adversarial Networks (GAN) can be utilised to simulate an evolutionary arms-race between a synthetic prey and predator.

Understanding art reception from eye movements using AI-generated artworks

The project examines how we can predict preference to visual artworks using eye movements of observers and artworks generated by deep neural networks. 

Cultural evolution of military camouflage uniform patterns

My PhD work focused on how camouflage uniform patterns evolved since the early 20^th century. The research uses methods from computer vision to establish similarity metrics between patterns and phylogenetics to model how patterns of allied / hostile countries have influenced each other’s designs.