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Jennifer Forrester works with aerospace partners to develop methods incorporating measurement data into automated design processes to inform design decisions. She investigates the effects of uncertainty on probabilistic performance, with an emphasis on the practical implementation of state-of-the-art methodologies alongside existing computational analysis codes. This enables machine learning based approaches to be used in geometric design. Jennifer has a background as a chartered engineer designing composite marine structures and leading consultancy projects for international clients. Her current research is part of the Rolls-Royce plc led COLIBRI project, which aims to improve design automation by integrating machine learning and artificial intelligence into design processes. Her work focuses on digital representation of geometry using discrete occupancy-based pixels and voxels, requiring practical means for the integration of existing boundary representations such as meshes used in CAD-based design and manufacturing specification. She has been involved in several high-profile projects and continues to be active in research funded by Rolls-Royce plc and the UK Government.
University of Southampton • Southampton, ENG, GB
Conducting research in computational engineering methods, focusing on design automation and integration of machine learning in design processes.