Rebecca WilsonPhD student
I graduated from the University of York in July 2014 having obtained a Masters of Mathematics MMath and in my final year I received the P. B. Kennedy prize for outstanding final degree examinations in Mathematics. During my undergraduate degree I took a range of modules, mainly concentrating on pure mathematics such as Group Theory and Analysis, and I found that I particularly enjoyed the Stochastic Processes modules that I covered.
I was attracted to the Centre for Doctoral Training at STOR-i due to the industrial focus and the opportunity to further my studies. I am looking forward to the challenges that will come with being part of the programme.My PhD research is focused on developing methods to detect corruption in high frequency Distributed Acoustic Sensing data, with particular interest in the application of such techniques in the oil industry. My work is supervised by Idris Eckley at Lancaster University and Tim Park and Rakesh Paleja at Shell.
Dynamic detection of anomalous regions within distributed acoustic sensing data streams using locally stationary wavelet time series
Wilson, R., Eckley, I., Nunes, M., Park, T. 15/05/2019 In: Data Mining and Knowledge Discovery. 33, 3, p. 748-772. 25 p.
- Changepoints and Time Series
- STOR-i Centre for Doctoral Training