Doctoral Student at the
Systems Biology Doctoral Training Centre
Email: matthew . willetts at dtc . ox . ac . uk Addresses:

Updated on: October 19, 2015
October 2015  Present: DPhil Candidate, Magdalen College, Oxford
October 2013  June 2014: 1st Class MSci in Physics, Trinity College, Cambridge.
Thesis: The use of hyperspectral imaging techniques to analyse Red Blood Cells
Supervisor: Professor Stephen Eliot
My masters thesis was on taking and using hyperspectral images of red blood cells (RBCs) to carry out a complete blood count (CBC), the standard blood test that describes their number and makeup. I used equipment far simpler than that used in standard automated methods. With various computer vision techniques I was able to write an algorithm to recognise the RBCs within the image, calculate their size, and, using hyper spectral analysis of haemoglobin absorption, calculate all the various quantities that form a CBC. This technique would enable a CBC to be done in minutes in a doctor's surgery, rather than requiring samples to be sent to a lab.
October 2010  June 2013: 1st Class BA in Physical Natural Sciences, Trinity College, Cambridge.
Specialising in Theoretical and Experimental Physics
Director of Studies: Dr Malte Grosche
September 2014  July 2015: Castastrophe Response Analyst, RMS
Worked on improving techniques for modelling hurricanes in real time and led the analysis for a major project on the effects of hurricane winds and storm surge on a wellknown transit system..
2013: Summer intern at BP in the Imaging R&D department
I worked on using information theoretic techniques to inform the design of seismic surveys. The aim for seismic surveys is to capture as much data as possible on the subsurface as densely and uniformily as possible. Information entropy increases with the uniformity and density of a probability distribution, so with some manipulation it can be used to calculate a proxy for survey quality.
2012: Summer researcher at Harvard under Prof Martin Nowak
I worked on spatial game theory  studying the prinsoners' dilemma in a population of players, some following a cooperative strategy and others acting as certain defectors, playing their neighbours on a lattice. The question I focused on is: do the edge cooperators do better than the edge defectors? If so, then it would be rational for the edge defectors to change strategy and cooperate, thus islands of cooperation can spread. There are instances where cooperation can spread but it depends on the lattice and the various parameters in the model, which corresponds to our intuition.
Profficient in R, matlab, Python and C/C++
Experienced in mathematical modelling and data analysis