Fin Brown works on several aspects of the Consilium Scientific data lifecycle, deploying a number of data extraction and cleaning processes, as well as producing visualisations to assist with final analyses. Fin recently graduated from the London School of Economics with a Master’s degree in Data Science, and also holds a Bachelor’s degree in Statistics, Economics and Finance from University College London. His research interests lie mostly in deep learning, with a focus on predicting mental health outcomes using longitudinal health data via Recurrent Neural Networks and novel image generation using Generative Adversarial Networks.
