The key challenges facing research, development and deployment of autonomous systems require principled solutions in order for scalable systems to become viable. This proposal intertwines probabilistic (Bayesian) inference, model-predictive control, distributed information networks, human-in-the-loop and multi-agent systems to an unprecedented degree. The project focuses on the principled handling of uncertainty for distributed modelling in complex environments which are highly dynamic, communication poor, observation costly and time-sensitive.

This project explores food safety issues and presents a prototype approach to evaluate and manage food safety especially in cross border supply chains involving best practices, international regulatory requirements and procurement strategies adopted by the food manufacturing firms.

This project explores implications of climate change on global supply network, which includes raw materials, platform, facilities including plant and geographical locations, product, employees, customers and supporting infrastructure. The effects of climate change, and a greater prevalence of associated extreme events, need to be included into supply network design for resilience. By integrating climate forecast scenarios with supply network configuration theories, a conceptual framework will be proposed for systematically identify and manage key sources of climatic risks in global supply network.

A manufacturing responsiveness auditing approach is being adapted in conjunction with UK salad vegetable producer G’s Growers to develop a more broadly applicable tool for assessing resilience of an operation and in the case of G’s to assess whether different operational disruptions can be absorbed effectively.