I am a PhD student in the machine learning group at the University of Sheffield. I study under the supervision of Professor Neil Lawrence.
My research interests are broadly centred around probabilistic machine learning in the setting of Survival Analysis. I look predominantly at how Gaussian Processes may allow us to infer risks associated with a large number of attributes.
I am a core developer of the GPy software that is under active development, GPy is a Gaussian Process framework written in Python. It tries to maintain an intuitive interface for working with Gaussian Processes whilst being heavily optimised and object orientated to maintain speed and to encourage participation from outside of the group. I mainly work on introducing non-Gaussian likelihoods to the framework and developing approximations, primarily the Laplace approximation, to integrate with the existing models within the framework.
Other public code can be found on my GitHub page github.com/alansaul with more to be released in the near future.
Paper Chained Gaussian Processes accepted at AISTATS 2016.
Visited Helsinki to work with Aki Vehtari on survival analysis and missing data models.
ContactSheffield Institute for Translational Neuroscience
385A Glossop Road
S10 2HQ, Sheffield, UK
Tel: (+44) 0114 2222271 Alan Saul
email: alan.saul (at) shef.ac.uk