Stochastic Modelling and Optimisation
Much of human intellectual endeavour is
directed to predicting and modifying the future. Initially this is attempted by
looking for patterns. Sophisticated methods for the study of patterns are
provided by mathematics.
Measurements and data are studied to suggest patterns, which are then modelled
mathematically. The predictions of the models are tested against further
observations and the models used to make decisions and modify future outcomes.
The applications of stochastic, or random, processes in engineering, finance,
biology and many other fields fit this paradigm. In all cases real world
measurements and data provide the foundations for theoretical models. These
models are then explored to make predictions and assist in improved decisions,
whether they are investment strategies, management policies in
telecommunications networks, or potential new avenues for cancer treatment.
We are associated with two groups that specialise in performing contract research and consulting with the defence sector, CDCIN, and the telecommunications sector and general industry,
TRC Mathematical Modelling.
|Matthew Roughan||Network tomography and traffic matrix modelling, Routing robustness, Compressive sensing, Privacy preserving data mining and management|
|Nigel Bean||Markov chains, Matrix analytic methods, Operations research, Mathematical modelling|
|David Green||Markov chains, Matrix analytic methods, Simulation modelling|
|Tony Roberts||Modelling stochastic dynamics|
|Joshua Ross||Mathematical biology, Mathematical modelling, Markov chains, Operations research, Stochastic modelling|