This is a page that I maintain myself to publicise my work and share code for download. I also have an entry in the online staff directory at the Université du Luxembourg. I am currently in Luxembourg as an Auxiliaire Scientifique to Tanja Schilling in the soft matter theory group; previously I postdoc'd in the KOMET 331 group in Mainz. I did my PhD in Leeds, co-supervised by Sarah Harris and Sheena Radford; and my other degrees in Edinburgh.
My research is mostly in the region of computational biology and physical chemistry. Right now most of my effort is spent developing novel simulation and search techniques.
I am interested in rare event calculations, particularly in time-evolving systems. The classic example is nucleation in a system with a time-dependent external driving force, such as an imposed shear flow. Rare event simulation is a special case of the wider field of searching and representing energy landscapes.
In a landscape search, the object is to characterise a system in terms of the states which it can occupy at equilibrium; with the idea that dynamics either at or away from equilibrium can then be characterised as paths through this landscape. In a rare event search, the object is to identify and characterise a subset of the available paths of a system, typically seeking out those which represent a dramatic change in the collective state. This path-based formalism makes more sense when considering dynamics off equilibrium, or when you have a clear idea of the type of event which is interesting.
I and Tanja have invented a method for calculating rare-event pathways off-equilibrium. You can read about it in context on the wikipedia page for "Transition Path Sampling", which I consider our method to be an extension (or revision) of, or you can download some example code here. The image of fractally generated tree branches (thankyou wikimedia) is intended as a poetic illustration of the spreading paths which a stochastic system can take through time.
Proteins can assemble to form linear filaments called amyloid fibrils. Molecular dynamics simulations of model amyloid fibrils can help us to understand how these toxic supramolecular aggregates form and spread. The image of interlocking peptide sidechains is taken from a set of molecular dynamics simulations which I carried out to explore some of the many configurations which are available for aggregates of even the smallest of peptides. You can read more about this on my publications page.