- Our team applies multidisciplinary theories and methods to diverse technology decision making approaches. This includes supply chain design, life cycle analysis and evidence-based decision making.
- We focus on data-driven project management and scheduling approaches that allow us to better integrate business rules and principles along the line of conventional project management.
- When we develop advanced decision-making tools, we consider various criteria with proper implementation of advanced techniques. This includes evolutionary algorithms, machine learning tools, and multi-method approaches.
- We specialise in integrating business logistics and engineering economic concepts while making capability sustainment decisions.
We provide effective solutions for managing uncertainties and risks in complex project/program environments while making technology decisions.
- more agile and accurate decision-making tools for various phases of product life cycles
- better approaches and software-embedded tools to enhance decision making for data-driven businesses, and
- improved autonomous systems and decision making tools for adapting both uncertain and dynamic data.
Our researchers provide evolutionary approaches with a focus on optimisation. We demonstrate finesse in combining and applying data science and financial modelling concepts while making a technology decision. Our development of robust project control tools considers multiple resource uncertainties within the overall material supply chain. We also have proven success in applying advanced machine learning and the integration of optimisation concepts for decision making.