I am a PhD candidate at the Artificial Intelligence Research Centre, CitAI, at City, University of London, working under the supervision of Esther Mondragón and Eduardo Alonso.
My research is focused on how we can integrate associative learning principles in deep learning (DL) models to make models that can generalise better and more robustly. Learning phenomena involves formation of complex associations, DL provides a natural framework to accommodate the representation of stimulus and associations. An important part of learning is how to represent and reuse knowledge, I will explore how we can use Convolution neural networks (CNN), a deep hierarchical architecture, to learn representations of stimuli at different levels of abstraction. Associative memory is another area of my research, how a given stimuli is stored and associated with related stimuli for retrieval later. I will explore how we can use deep associative neural architectures with their hierarchical structure for representation of associative memory. I will also be researching attention in learning theory and how to integrate it in DL models, inspired by the recent success of the Transformers architecture.
I obtained my MSc in Artificial Intelligence from City, University of London and have a BSc Hons in Computing science from University of Greenwich, London. Prior to embarking on my research journey, I worked as a Solution architect at Rank group, designing enterprise applications for the gaming platform. Before joining Rank Group, I worked as a tech lead at Bank of England, leading a team of developers to build an online platform for rules that regulate the financial services.