PhD in Statistics, Oxford-Warwick Statistics Programme, 2016-2020
Deparment of Statistics at the University of Oxford, UK
Masters in Mathematics (Part III) 2015-2016
University of Cambridge, UK
Mathematics Tripos 2012-2015
University of Cambridge, UK
I am a Postdoctoral Research Fellow at the University of California San Diego working with Armin Schwartzman. I work on developing statistical methods with applications in Neuroimaging, Genetics and beyond. For more details see my CV. If you're interested in collaborating or have a question about my work please feel free to email me (sdavenport(AT)health.ucsd.edu).
My research focuses on develping methods for analysing spatial data with a particular focus on multiple testing via parametric (i.e. Random Field Theory) and re-sampling based methods. My interest in Random Field Theory (RFT) stems from the huge potential for application across a variety of fields and the beauty of the underlying mathematics. Recently this has been a matter of controversy in the neuroimaging community, primarily because RFT methods have been applied widely without proper regard for the underlying assumptions. However it turns out that a number of these assumptions are unnecessary and can be dropped (by modifying the theory). My work focuses on developing RFT (and other) methods that provide correct control of the false positive rates and allow for better, more powerful inference. Non-parametric methods provide another important means of analysing spatial data especially when the statistics of interest are not tractable parametrically. Combining RFT and non-parametric approaches can increase the power of inference whilst maintaining method validity.