My research interests are in systems integration and innovation in built infrastructure. The vision is of radically improving the delivery of complex infrastructure projects. The ambition for the next five years is to identify risk in and build resilience into engineered systems by developing new ways to visualize and understand relationships between parts and the systemic consequences of changes in complex product systems using digital technologies.
Achieving the vision will need a team that brings mathematicians and computer scientists together with scholars of engineering to develop the basis for a new generation of tools and techniques for managing change through the life of complex product systems. I anticipate this bringing learning and innovation from other industries into construction; and exploring fundamentally new approaches that will utilise a range of machine learning, graph theory, systems dynamics and scenario planning techniques. I am working with the Laing O'Rourke Engineering Excellence Team to shape this trajectory of research on systems integration techniques to examine system verification methods with information models; and design in cyber security and system resilience from the beginning.
I'm interested in supervising PhDs that bring systems engineering and innovation in infrastructure. Please contact me if you meet Imperial's admission criteria and are interested in this research area. Topics, include, but are not limited to:
1) Identifying interdependencies in complex engineering systems by visualizing relationships
This PhD research develops a decision-support tool for engineers and managers that are involved in the late design and production stages, helping them to visualize and understand the systemic consequences of proposed changes across engineering disciplines. It uses graph theory methods (such as the Design Structure Matrix and/or social network analysis) to map the interdependencies between the assets represented within a BIM model in relation to physical connections, mass flow, energy flow and information flow; and then predictive data analytics, drawing on evidence from previous cases, to explore the potential interactions and consequences of change in order to develop an ex-ante decision support tool for change management.
2) Construction engineering and the general theory of systems integration
This PhD research takes the mathematical formulae developed in the general theory of systems integration (GTSI) and tests their validity in relation to the civil engineering context. The work will include evaluating the logic of the general theory; and empirically testing it against real-world data from complex engineering projects.
3) Safety in the delivery and operation of complex systems
This PhD research applies the system theoretic accident model (STAMP) to analyse the chains of events that occur across built infrastructure systems rather than seeking root causes, and sees reliability and safety as different properties of systems. The novelty lies in extending this existing theory to consider the particular nature of built infrastructure systems as complex cyber-physical systems.
4) Verification and validation of digital engineering models
This PhD research develops an approach for rapidly verifying and validating digital engineering models, using models that are created using open standards such as Industry Foundation Classes (IFCs). It develops new techniques to ensure their verification and validation against requirements; design intent; and built infrastructure. The research aims to improve the verification of model data using a systems engineering approach. The first step will be to collate data from previous projects on verification challenges. The second step will be to work with IFC and XML data and seek to automate the verification of models that have been developed in different software packages. This work will build on existing tools and approaches, but seek to develop new techniques to systematically analyse differences between models; and predict where such differences may occur.