I belong to the Machine Intelligence laboratory in the Department of Engineering of the University of Cambridge. I am also a research fellow at Trinity Hall.

My research is concerned with the application of Machine Learning techniques to Computer Vision. Every second, gigabytes of data arrive at our eyes, yet our brain effortlessly translates this into concise descriptions of the world enabling us to perform everyday tasks. As information engineers, our responsibility is to manage the overwhelming quantities of information available to us and in my research I have taken inspiration from humans to learn the mappings between high-dimensional image data and a problem-specific output space. Such mappings are learnt discriminatively from a set of labelled training data using the Bayesian rules of inference to pragmatically account for uncertainty, incorporate prior knowledge and set parameter values. The benefits of learning mappings (as opposed to defining a model of image generation) are efficiency and the ability to generalize when images change in some previously unseen way. See my publications list or some videos for more information!

Efficient visual interfaces
I have recently been collaborating with the Dasher project to create a simple interface for text entry requiring just a web-cam. This project has had some press attention!.