Imperial College London

Ms Claire Baker

Faculty of EngineeringDyson School of Design Engineering

Research Associate



c.baker17 Website CV




Dyson BuildingSouth Kensington Campus





Claire is a PhD student whose current research, the AutoTriage project, lies at the exciting intersection of the automotive, medicine and engineering industries. She is investigating the feasibility of predicting Traumatic Brain Injury severity in Road Traffic Collisions using on-board vehicle sensors, with the overarching aim of improving Emergency Service response and trauma outcome.

She is supervised in this project by Dr Mazdak Ghajari (Imperial College London's Dyson School of Design Engineering), Prof. David Sharp (Imperial College London's Computational Cognitive Clinical Neuroimaging Lab) and Prof. Mark Wilson (Imperial College London's Department of Medicine) and Dr Phil Martin (Transport Research Laboratory Ltd). She is supported and jointly funded by Transport Research Laboratory Ltd and the Engineering and Physical Sciences Research Council.

As well as being hosted by Design Engineering during her PhD, Claire is a member of Imperial College London's multidisciplinary Centre for Doctoral Training program in Neurotechnology, from which she graduated with a distinction in her research masters in 2018. Claire's background is in Astrophysics, which she studied during her undergraduate masters at the University of Southampton. She graduated in 2017 with a first class honours in Physics, completing her final year research at Harvard University's Smithsonian Center for Astrophysics. 



Baker CE, Yu X, Patel S, et al., 2023, A review of cyclist head injury, impact characteristics and the implications for helmet assessment methods, Annals of Biomedical Engineering, Vol:51, ISSN:0090-6964, Pages:875-904

Yu X, Baker C, Brown M, et al., 2023, In-depth bicycle collision reconstruction: from a crash helmet to brain injury evaluation, Bioengineering, Vol:10, ISSN:2306-5354, Pages:1-16

Yu X, Baker CE, Ghajari M, 2023, Head impact location, speed and angle from falls and trips in the workplace, Annals of Biomedical Engineering, ISSN:0090-6964, Pages:1-16

Posirisuk P, Baker C, Ghajari M, 2022, Computational prediction of head-ground impact kinematics in e-scooter falls, Accident Analysis and Prevention, Vol:167, ISSN:0001-4575, Pages:1-11


Baker CE, Montemiglio A, Li R, et al., 2022, Assessing the influence of parameter variation on kinematic head injury metric uncertainty in multibody reconstructions of real-world pedestrian vehicle and ground impacts, 2022 IRCOBI Conference, Pages:393-394, ISSN:2235-3151

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