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 and jump processes) 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 high-frequency data, probability of default, agent-based models of the distribution of wealth, Fourier-transform spectroscopy, molecular simulation and soft condensed matter theory. In the latter two areas first I did hybrid quantum-classical models of proteins and ab initio calculations of smaller molecules, then coarse-grained models of liquid crystals with Monte Carlo or domain-decomposition molecular dynamics on massively parallel architectures, including the development of algorithms, code, force-field parameters and molecular graphics. Other keywords are mathematical modelling, applied mathematics, high-performance computing, and complex systems, where aggregate behaviour emerges from the interaction between many component parts.