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.
My research interests are in the use of deep neural networks and probabilistic models on large medical datasets, such as medical imaging or electronic health records. I’m interested in projects that push the state of the art in deep learning methods to make an impact in healthcare.