Alumni

Here you can find details of STOR-i alumni including information about what they're up to now.‌

 

Helen Barnett 

Upon completing my PhD in 2017, I started my post as a Senior Research Associate in Medical and Pharmaceutical Statistics at Lancaster University. My research is funded by Janssen Pharmaceutica, who were the industrial partner for my PhD with STOR-i. I am working closely with Janssen on the topic of dichotomisation of continuous biomarkers, a very interesting and relevant subject in the area of personalised medicine.

 

Lawrence Bardwell

My PhD looked at methods to efficiently perform inference for changepoint models in high-dimensional time series. It was industrially sponsored by British Telecom and I was supervised by Idris Eckley and Paul Fearnhead from Lancaster and Martin Spott from BT.  

 
I now work as a Statistician at an educational consultancy company, AlphaPlus consultancy.
 
 

Matt Ludkin

Matt Ludkin

I completed my PhD at STOR-i in 2018 under the supervision of Prof. Peter Neal and Prof. Idris Eckley with sponsorship from Ralph Mansson at the Defense Science and Technology Laboratory (DSTL).
 
My PhD thesis, titled "The autoregressive stochastic block model with changes in structure", looked at statistical models for network data collected through time. Specifically, models to detect if the group structure within the network had changed.
 
I now work as a senior research associate with Dr Chris Sherlock on the EPSRC project "New developments in non-reversible Markov chain Monte Carlo" (EP/P033075/1). Traditional reversible MCMC aims to draw samples from a target distribution by simulating a Markov chain whose stationary distribution is the target. One downside to reversible algorithms is that they lose a sense of direction in regions where the target is flat. This leads to slow exploration. Conversely, non-reversible methods keep a sense of direction. Current methods have great potential but practical problems limit their usability. My research currently aims at creating new non-reversible algorithms that are more efficient than standard MCMC and can be applied to real problems with ease.
 
Link to my website: www.lancaster.ac.uk/~ludkinm
 
 

Paul Sharkey

I completed my PhD in 2018 under the supervision of Jonathan Tawn, Simon Brown (Met Office) and Hugo Winter (EDF Energy). My PhD research focused on developing multivariate methods for modelling extratropical cyclones that incorporated the meteorology of these weather systems. 
 
Since leaving STOR-i, I became a statistician at JBA Consulting as part of the Flood Risk Science team, where I work with a group of specialists from the physical sciences to model impacts arising from coastal, river and weather extremes. This has allowed me to continue research into extreme value statistics, and explore new and exciting environmental applications that could benefit from this methodology.