My name is Sam Tickle, and I am a doctorate researcher at the University of Leeds, and my research concerns the detection of change in signals.
At first glance this may seem somewhat innocuous and abstract, but the uses for change detection are incredibly ubiquitous, especially for a company such as BT, where spotting a small shift in a single data series in efficient fashion can make all the difference in mitigating a future operational failure, containing a denial of service attack, or simply maximising speed of customer service.
Changepoint detection has been used elsewhere to great effect, including, health care, finance, environmental science and large-scale retail. The advent of the Big Data Age, however, has presented something of a challenge for existing changepoint methods, where datasets of interest can have millions of variates in addition to a high density of observations.
I am therefore specifically interested in efficient changepoint detection for data streams. This project contains two broad phases
The first being to examine the means of speeding up current techniques, and
The second to pioneer novel approaches to multivariate changepoint detection.
We have had some success with the first phase already, with potential for real-time high-dimensional change detection now a reality. The paper, and computer package, for this will be appearing soon.