I have an MEng in Biomedical Engineering from Imperial College London. My master’s thesis was on the use of deep reinforcement learning for tracking neurons in microscopy images, and I presented this work at MIDL 2019. Other topics I covered at Imperial include image and signal processing, computational neuroscience, and machine learning. After graduating I worked for two years as a machine learning engineer at Samsung Research, on the compression of deep convolutional networks for mobile device inference, and efficient neural network design. Other projects I worked on at Samsung include work with GANs, and computer vision tasks.
I am working on my DPhil supervised by Christoffer Nellåker in the Big Data Institute and Andrew Zisserman in the Oxford Visual Geometry Group. My research focus is on the diagnosis of rare genetic disease from face images. I am using unsupervised approaches to deep learning on datasets with long-tailed and open-ended distributions.