Dr Alexandra Brintrup

Manufacturing | The University of Cambridge

Dr. Alexandra Brintrup led the Manufacturing theme for Pitch-In. She is a Lecturer in Digital Manufacturing at the University of Cambridge’s Engineering Department.

She has obtained her PhD from Cranfield University for her work in Genetic Algorithms in 2007. She then worked at the ABN AMRO Bank as a quantitative analyst, before joining the Distributed Information and Automation Lab (DIAL) in Cambridge for her postdoctoral studies in the development of multi-agent systems in manufacturing and supply chains.

She was later appointed as research fellow at the Complex Agent Based Dynamic Networks (CABDyN) research centre at the University of Oxford, where she studied supply chains from a complex networks perspective.

Between (2012–2015) she was a University Lecturer at Cranfield University. She then re-joined the Institute for Manufacturing at Cambridge as a Lecturer is leading the Manufacturing Analytics Research within DIAL.

Alexandra is a fellow of Darwin College. Having trained as a manufacturing systems engineer and then embarking on a research career in artificial intelligence, she is fascinated by the merger of the two.

Her research interests include:

  • Predictive analytics and machine learning, especially for predicting and handling emergence and uncertainty in supply chains and manufacturing.

  • Development of autonomous and scalable optimisation and distributed decision making technologies, particularly with nature-inspired algorithms and multi-agent systems.

  • Identification of emergent patterns in manufacturing and industrial systems, particularly in relation to robustness, resilience and quality outcomes.

Over the past decade Alexandra has advised policy makers, served in a number of scientific committees, and worked with various industrial partners, including Boeing, Rolls Royce, Jaguar Land Rover, Suzuki and Procter and Gamble in these areas.

She is a member of the All Party Parliamentary Groups in Artificial Intelligence and Data Analytics, EPSRC Early Career Forum in Manufacturing, the US based CASN-RA group, and IEEE.

< Projects >


Utilising the Internet of Things to enable autonomous supply chain management – connecting existing research to review the technical feasibility of real life deployment and support industry adoption.

IoT driven graphic

This project’s aim was to develop a tool that helps manufacturers determine what types of goods could be more suitable for Internet of Things (IoT) – driven personalisation versus those where human intelligence needs to drive customisation.