Computational science or scientific computing (sometimes called eScience or eResearch) applied to financial mathematics and statistical physics. Currently my main interests are stochastic processes (in particular stochastic volatility, Lévy processes and continuous-time random walks) and the numerical solution of pricing equations for barrier options and other path-dependent derivatives using fluctuation identities in Fourier-z and Fourier-Laplace space or Monte Carlo, but I have been working also on model calibration, machine learning, algorithmic trading, empirical studies of high-frequency data, and agent-based models. I have done the latter in economics (distribution of wealth) and, predominantly, in soft condensed matter theory (molecular simulation), where I have specialised first in quantum/classical models of proteins and ab initio calculations of smaller molecules, then in coarse-grained models of liquid crystals using Monte Carlo or molecular dynamics with domain decomposition on massively parallel architectures; this includes the development of algorithms, code, force-field parameters and Open GL molecular graphics. Other keywords are high-performance computing, applied mathematics, and complex systems, where aggregate behaviour emerges from the interaction between many component parts.