Bio
Tom Savage is a PhD candidate within the Sargent Centre for Process Systems Engineering at Imperial College London. He currently works in the Optimisation and Machine Learning for Process Systems Engineering (OptiML PSE) group and has obtained a BEng in Chemical Engineering from the University of Manchester, and an MPhil in Chemical Engineering & Biotechnology from the University of Cambridge. His previous work has included the design of national-scale knowledge graph-based digital twins, the optimisation and control of chemical processes, and design of next-generation of chemical reactors. He also works with the Linacre Institute, a charity helping talented and disadvantaged state-school students in the North of England gain access to education at leading universities such as Oxford, Cambridge, and Imperial.
Research interests
Tom’s current work focusses on two main themes. Firstly, the use of data-driven optimisation to design highly parameterised chemical reactors. As additive manufacturing has enabled the construction of more complex reactors, there exists a need to optimise in these larger design spaces. By applying methods that take advantage of lower quality but computationally cheaper fluid dynamics simulations, more complex reactor designs can be considered. Optimal reactor geometries are 3D printed and their performance validated, demonstrating their potential to improve the sustainability of future chemical processes.
Secondly, his research concerns the design of future energy policies to support the use of low-carbon technologies. By accounting for the inherent uncertainty around technologies such as wide-scale hydrogen or electrification, his work removes barriers to their implementation by quantifying their potential to contribute towards net-zero. Through the use of robust optimisation, a variety of optimal solutions can be provided to policy-makers, each entailing a different level of risk.