I'm a data scientist with a background in statistical physics. I'm interested in understanding the collective behaviour of many interacting components in a variety of contexts. In particular using tools from statistical mechanics and network theory.

I am trying to understand how to vary the shape and interactions between colloidal building blocks to control the assembly of what we want, while avoiding what we don't want.

The statistical mechanics of networks involves studying large ensembles of networks that share particular properties to see what features are unique and what features are common.

The principle tool underlying my research is Monte Carlo. I apply a wide range of existing techniques and develop new methods when the problem requires it.

Kinetically Constrained is my blog on statistical mechanics related topics. You can see some scale invariance demonstrations there, which I'm going to put on this site shortly as well.

Some demonstrations on the features of a system near to its critical point, such as scale invariance, universality and the renormalisation group. Critical fluctuations require special techniques to study and could prove useful for self assembly through critical Casimir forces.