PhD Student
Room G33,
School of Computer Science
Kilburn Building,
The University of Manchester


I am a final year PhD student in the Machine Learning and Optimisation Research Group in the School of Computer Science at The University of Manchester. I work under the supervision of Magnus Rattray.

My research interests include many aspects of machine learning and computational biology. I am particularly interested in all aspects of Bayesian inference including the development of improved approximate inference algorithms.

However, the particular focus of my PhD project has been on inference in sparse factor analysis models, motivated by the problem of trying to infer simple models of transcription networks.

A copy of my current Curriculum Vitae can be found here.

I am grateful to receive funding from an EPSRC PhD scholarship and a PhD scholarship supported by Manchester alumni through Your Manchester Fund.


Kevin Sharp and Magnus Rattray (2010): Dense Message Passing for Sparse Principal Component Analysis,
in Y.W. Teh and M. Titterington (Eds.), Proceedings of The Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010, JMLR: W&CP 9, pp 725-732 , Chia Laguna, Sardinia, Italy, May 13-15, 2010,
[pdf] [bibtex]
M. Rattray, O. Stegle, K. Sharp, and J. Winn (2009): Inference algorithms and learning theory for Bayesian sparse factor analysis,
Journal of Physics: Conference Series, 197:012002 (10pp), 2009.
[pdf] [bibtex]


Matlab code implementing the Dense Message Passing algorithm described in the AIStats 2010 paper mentioned above is available here (32KB).

This download includes everything required to reproduce the results in the paper for the dense message passing algorithm applied to synthetic data. Please see the README.txt file within the download for instructions.

To reproduce the gene expression data results and the results for the other algorithms you will also need to download data and code from the appropriate websites. Please see the README.txt file within the download for instructions about how to obtain these.

If you have any problems, please email me. I will be happy to help.


Dense Message Passing for Sparse Principal Component Analysis
(AIStats 2010). A video of the talk is available at
Dense Message Passing for Sparse Principal Component Analysis
(SuSTaIn workshop: Sparse structures: statistical theory and practice) [Slides]