My main research interest is the control of stochastic systems, most notably service control in queueing systems.
Defensive surveillance is of great importance in the modern world, motivated by the threats faced on a daily basis from adversarial agents. Technological advances are continually being made to mitigate these threats. Consider a surveillance resource responsible for a number of randomly evolving public areas, such as a camera observing different areas of a busy train station. Assume the resource can screen subjects individually from any area it chooses in terms of their identity. The limitation of the resource means that it must be utilised as effectively as possible. Adversaries wish to enter an area, complete an illicit activity, for example a terrorist attempting to plant a bomb, and leave before detection. These agents are often strategic, wishing to remain covert in amongst the public so as to minimise their chance of detection. Controlling such technology in order to mitigate these threats is both important and challenging. The PhD research models such scenarios using queueing theory and game theory, a mathematical combination rarely found. The objective is to identify optimal surveillance policies with respect to the strategic nature of adversaries which maximise their probability of detection. To my knowledge, this is the first attempt to study this general problem using this methodology. It is hoped this exciting approach will inspire future researchers to extend the research field. Moreover, it is hoped the work will lead to real operational tools which combat adversarial threats, giving positive financial and social returns and help to maintain the society we live in.