About Me

David Greenwood, MSc MA CANTAB
PhD Student, Dependable Systems Engineering Group, University of St Andrews

I am a PhD student of the Computer Science Department at the University of St Andrews, UK and my research expertise comprises socio-technical modelling and analysis for systems engineering. I work on a major UK strategic initative called the Large-Scale Complex IT Systems project with Prof. Ian Sommerville and we are exploring the socio-technical issues that affect the engineering and operation of Large-scale IT systems in corporate settings. Prior to obtaining a PhD position I worked as an Enterprise Risk Consultant at Deloitte.

For a high-level overview of my PhD work see this poster that I created for the LSCITS public symposium.

My work on responsibility modelling for identifying threats to the dependability of coalitions-of-systems (coalitions-of-systems are composed of technical components and human / organisational agents with differing interests) was awarded 'best paper finalist' at the Sixth IEEE International Conference on System of Systems Engineering. My work on using network analysis to analyse socio-technical models of system deployments won the ISSS (International Society for the System Sciences) Anatol Rapoport Award for best student paper in a quantitative systems science.

The academic value of my work stems from its contributions towards the development of scalable techniques for modelling and analysing large complicated socio-technical systems. Socio-technical analyses have typically involved interpretive analysis, whereas the approaches I have been developing are unique within socio-technical systems engineering as they comprise the development of models that are analysable algorithmically. A key benefit of my approach is that systems that are either too large or complicated for an individual to understand, using interpretive analysis, may become analysable using the processing power of modern computers and advances in algorithmic analysis.

The practical value of my work stems from the fact that it helps organisations become aware of the socio-technical intricacies and interdependencies of the services they consume (or offer). One of the benefits is that it enables the systematic identification of socio-technical risks (failure modes) in situations where organisations were previously unable to do this. Another benefit is that it enables the troubleshooting of situations that were previously misunderstood due to their scale or socio-technical intricacy. This work has been recognised as particularly valuable due to the increasing prevalence of distributed models of work supported by complex IT systems (e.g. utility computing, outsourcing, multi-agency work, complex supply chains).