I am interested in the fundamental mechanisms in the brain that give rise to learning, cognition, behavior, intelligence and consciousness. Neuroscience has made great progress towards understanding how the brain functions at the molecular, cellular and biological levels. However, describing brain function at the network level is still very difficult because the connectivity pattern between individual brain cells, or neurons, is not well understood.
The "connectome" is a network diagram of the connections in the brain. Understanding how neurons connect to each other at the synaptic level is an essential step towards an understanding of brain functions such as learning, memory and cognition.
My research is currently focused on developing tools for connectomics; with the goal of measuring every synaptic connection between every neuron in a small volume of the brain. As part of a collaboration between the Pfister and Lichtman labs at Harvard University I am helping to develop software tools, machine learning techniques and computer vision algorithms for electron microscopy (EM) image analysis, automatic segmentation and neuron annotation. We are developing an open source image processing pipeline for segmenting EM images in very large datasets, up to petabyte (PB) scale. More details are available at www.rhoana.org.
I completed a PhD in Neuroinformatics in 2012 and an MSc (Distinction) in Bioinformatics in 2008, both at the University of Edinburgh. Before that I worked in industry for several years in the UK and New Zealand, where I graduated with a BSc (Hons, 1st) in Computer Science from the University of Canterbury in 2000.