Allison Clement

Hardworking and motivated professional with a strong mechanical and biomedical engineering background. Specifically interested in automation, computational modelling (finite element analysis) and artificial intelligence applications.

I currently work as a Research Engineer/Physicist at Sunnybrook Research Institute. As apart of the Orthopedic Biomechanics Laboratory, I developed computational techniques to create a better understanding of the biomechanics of the skeletal system and developing technologies for diagnosis/ treatment of disease. 

I currently am working on developing predictive networks to derive a face from skull using metadata and CT images (Pytorch). I also helped to develop a UNet for automated skull reconstruction to generate surgical implants (MICCAI 2021). I work with an open-source facial recognition pipelines to create 3D maps from 2D images (Python, Docker) to create surgical templates for nasal reconstruction surgery. I work on clinical studies for shoulder reconstruction and develop automated methods for implant guides intraoperatively. In my current role I also preform data collection and analysis of mechanical experiments to determine the effect of fracture healing drugs on femur biomechanics, cancer on spinal stability, and craniofacial surgery techniques on force distribution. 

As a part of the Medventions Innovation Program at Sunnybrook Hospital I worked with a multidisciplinary team, to develop technologies for improving patient outcomes. This roll includes active research by interviewing/shadowing clinicians to determine areas of improvement accompanied by in-depth literature reviews and evaluation of the market space. Our team plans to develop a company which will create a method using NLP techniques to analyzing clinical notes to improve patient care. 

Masters of Biomedical Engineering at the University of Toronto with an additional specialization in Musculoskeletal Sciences. Undergraduate degree in Mechanical Engineering.

My master thesis: Medical imaging characterization and computational fracture evaluation of the cancerous spine, included automated tumor quantification (pyradiomics, scikit-learn, Python), mechanical testing and finite element modeling (Abaqus, Linux, FEM).