Since October 2023 I have held a senior research staff position in the Department of Orthopaedic Surgery at the University of California, San Francisco. My main role has been leading the delivery of OrthoCAP, a remote iOS application to collected patient motion and health data. This has been a complex feat within the realm of a university hospital requiring careful collaboration and strategic planning with researchers, surgeons and external stakeholders to correctly design the application's features. I have liaised closely with practicing surgeons to collect clinical information of value to implement into the application and UCSF data security teams to ensure HIPAA and ethical standards are maintained.

In addition I am actively involved in spinal research projects with orthopaedic and neurosurgeons, focusing on adult spinal deformity surgery effectiveness and cervical spine patient  condition characterisation using motion analysis methods. I have led on the acquisition of a new motion capture system for the lab fro 20% below budget. I take initiative in the group's organisation strategies by implementing analysis code version control and SOP on databases.  Finally  I provide supervision assistance to MD, PhD and postdoctoral members of our team, advising them on best research practices and ensuring robust data collection and management.

Kinematic composite score for assessing musculoskeletal impairments

Sex-based differences in chronic lower back pain patients

From April 2022 to September 2023 I developed, tested and ran a computational biomechanical pipeline combining state of the art musculoskeletal modeling and predictive simulation software (OpenSim) to evaluate the the postoperative effects of specific RTSA surgical placement, designs and patient scapular morphology. By utilising available commercial designs, computational anatomy techniques, such as medical image segmentation and statistical shape modelling, and the biomechanical pipeline an in-silico patient study was performed to investigate the effect of morphologic variability and assist in the optimisation of future surgical technologies and techniques.

This study was accepted for a podium presentation and Business Innovation Competition at the 2023 ORS Annual Meeting in Dallas, TX. The next stage of this project involves generating a large dataset of possible morphological, design and surgical perturbations through setting up the simulation framework on HPC Clusters to generate the data efficiently.

I designed this workflow by observing and discussing with orthopaedic surgeons to interpret their needs as well as gaining deep understanding of the latest developments in the field of orthopaedic technology.

This novel study has been published in the Journal of Orthopaedic Research as of January 2024.

A large part of my doctoral work relied on developing a model that would charectarise the response of the cervical spine to high energy axial impacts. I developed an experimental and computational framework that estimated and verified the necessary model parameters that allowed correct approximation of measured experimental motion. By verifying computational models with precise experimental data that replicated the real world system under investigation I was able to create a physiologically plausible model with as much ground truth data as possible. 

This study was published after peer review in PLOS ONE in 2019 and presented at the 2018 World Congress of Biomechanics.

Collaborated alongside orthopaedic surgeons and biomedical engineers to conseptualise and carry out a mechanical study to evaluate the potential for novel patellar fixation strategies that would reduce trauma to patients. Was part of the data collection team and was the lead far the data processing, analysis and visualisation.

 We were successful in publishing this paper in the peer reviewed journal Injury in 2020.