I am primarily interested in machine learning and its intersections with complex applications and theory. My current research interests are focused in leveraging insights from optimization and neural computation to interpret and innovate on Artificial Neural Networks. I am interested in novel methods for applying deep learning to neuroimaging data, especially drawing from distributed learning for performing efficient and privacy sensitive analyses in large scale, collaborative settings. I am additionally interested in the use of information theory for training and interpreting neural networks, the application of complex network theory principles to modelling neural dynamics, and drawing inspiration from neuroscience to innovate with artificial neural networks and vice-versa.