I have been working in a broad range of subjects including fluid-structure interaction, optimal control for fluid dynamical systems, Gaussian Process (GP) for machine learning, and optimisation using surrogate models, such as neural network, support vector machine and GP regression.  My scientific background lies in Applied Mathematics and Computing, and I have extensive modelling and simulation experiences in both academia and industry, and teaching experiences in Calculus, Linear Algebra, Probability and Statistics, and Finite Element Analysis.