David Edmunds

David Edmunds has a diverse range of work experience in the fields of machine learning and medical research. David is currently a Senior Machine Learning Scientist at Hyperfine, starting in April 2021. Prior to this, David worked at CCDS as a Machine Learning Engineer from November 2019 to April 2021. In this role, they developed an end-to-end clinical ML inference pipeline for COVID-19 risk prediction and worked on cervical spine fracture detection. David also played a critical role in developing and maintaining internal ML Python libraries for medical imaging data.

From March 2017 to November 2019, David served as a Postdoctoral Research Fellow at Massachusetts General Hospital and Harvard Medical School, where they applied deep learning and AI methods to medical image analysis. David implemented a state-of-the-art convolutional neural network for automatic segmentation of the diaphragm on real patient lung CT images.

Prior to their research at Massachusetts General Hospital, David worked as a Postdoctoral Research Fellow at The Royal Marsden NHS Foundation Trust from July 2014 to March 2017. Here, they designed a cross-platform software tool for 3D visualization and analysis of radiotherapy-related risks. Additionally, they conducted a successful clinical trial for monitoring breathing motion using the Microsoft Kinect v2 3D depth sensor.

David's academic journey began as a PhD student at Imperial College London, where they focused on "Coarse-Grained Molecular Dynamics" from October 2010 to July 2014. David'sresearch involved simulating the behavior of carbon molecules on an atomic scale, utilizing high-performance computing in a Linux-based supercomputing environment.

Overall, David Edmunds possesses strong expertise in machine learning, medical imaging, and computational research.

David Edmunds completed their education in a chronological order. David first attended the University of Warwick from 2004 to 2008, where they obtained a degree in MMathPhys, with a focus on Mathematics and Physics. Following that, they went on to study at Imperial College London from 2009 to 2010, earning a Masters degree in Theory and Simulation of Materials. Finally, from 2010 to 2014, they pursued a Doctor of Philosophy (PhD) in Physics at Imperial College London.