Academic staff in AMOR are actively involved in a large number of research projects, some funded by UK Research Councils, UK industry or Defence Laboratories. These research projects can broadly be divided into five areas detailed below.

Operational Analysis/Research

Between them the AMOR staff have many years of experience of analysis in the public sector and defence industry and have strong links with the MoD's Directorate of Analysis, Experimentation and Simulation, the Defence Procurement Agency, Dstl, and many defence companies including major training and simulation companies in both the UK and the US . Specific research themes include:

• Mathematical and agent based models of conflict including peacekeeping. The application of Bayesian Belief Networks to support military decision making
• The analysis of simulation for infantry training, including evaluation of the applicability of virtual simulation technology for navigation
• Commercial games software as a tactical training mechanism
• Mission training through distributed simulation
• Capability analysis

Many of these activities make extensive use of the Simulation and Synthetic Environment Laboratory.

Scientific Computation

Members of AMOR have wide expertise in the field of Scientific Computation: the design, development, implementation and application of computer models applied to problems in science and engineering. Specific research themes include:

• Automatic Differentiation (AD)
• Computational Fluid Dynamics (CFD)
• Approximation & Data Fitting
• Optimisation
• Scientific Visualisation

Mathematical Modelling & Applied Mathematics

The AMOR group maintains its historic interest in mathematical modelling and applied mathematics with work on:

• Nonlinear bubble dynamics
• Scattering and diffraction of waves
• Functional & Geometric Design
• Depth profiling of thin-film materials
• Biological fluid mechanics

Statistics

We have experience in both methodological and applied statistical research, much of it in the area of multivariate (in the broadest sense) statistics. Specific methodological interests include:

• Response surfaces
• Sampling properties of both eigenvalues and projected coordinates in descriptive multivariate methods.

Intelligent & Decision Support Systems

We have a small but expanding research group in this area. Generally, our activities involve the development of decision support systems and intelligent systems, and we are particularly interested in military, industrial and health applications. The methods employed include Bayesian networks, influence diagram decision networks, hidden Markov models and neural networks.
Further details are available here.