I am a lecturer in the department of Computer Science at the University of York with a particular focus on autonomous systems. My work concerns how/if we can guarantee that such systems will operate as we would like them to, not only from a safety perspective but also with respect to human expectations. This work combines machine learning, probabilistic model checking and modelling more generally and is, by it's nature, multi-disciplinary.

Previously I worked as a senior post doctoral researcher within the Trustworthy Autonomous Systems Node in Resilience at the University of York where my research considered how we might improve autonomous systems through a consideration of social, legal, ethical, empathetic and cultural norms.

As part of the Trustworthy Adaptive and Autonomous Systems & Processes (TASP) research team I am involved in the development of tool-supported formal approaches for the engineering of adaptive and autonomous systems and processes with a particular interest in probabilistic model checking.

Having completed a PhD in control systems engineering in collaboration with Jaguar Cars, I moved into industry where I designed a number of bespoke web-based software solutions as well as a product suite for local government focused on governance, risk and compliance. During this period I also provided consultancy services for the management and delivery of software projects.

I returned to academia in 2014 and undertook a DSTL funded PhD which considered the formal verification of socio-technical systems in which human behaviour introduces variation and flexibility in published workflows. I work with stochastic models, in particular Markov chains, which may be analysed with probabilistic verification tools such as PRISM.

Having completed my PhD I worked on a second DSTL funded project which considered how Natural Language Processing could be integrated with probabilisitc models to improve the accuracy of decision centered tasks where information regarding the operational environment is encoded in unstructured forms.