Contact details
Address
Northampton Square
London EC1V 0HB
United Kingdom
About
Overview
Mpagi Kironde is a PhD student at the Artificial Intelligence Research Centre (CitAI), under the supervision of Dr. Esther Mondragón and Professor Eduardo Alonso. Mpagi's research focuses on integrating associative learning principles into deep learning (DL) models. This innovative approach is anticipated to foster the development of systems that can generalize with greater efficacy and robustness. The learning phenomena he is exploring involve the formulation of complex associations; in this regard, DL serves as a conducive framework for encapsulating both the representation of stimuli and their intricate associations
A facet of Mpagi's research is to decipher the optimal methods to represent and reuse knowledge within AI systems. To this end, he is delving into the potentials of Convolutional Neural Networks (CNN), a hierarchical architecture, to facilitate the learning of stimuli representations across varying levels of abstraction.
Mpagi’s research also focuses on associative memory, his investigations are centered on understanding the mechanisms through which a stimulus is stored and then associated with related stimuli for subsequent retrieval. Leveraging deep associative neural architectures, Mpagi is working to enhance the hierarchical structure for the representation of associative memory.
Qualifications
- BSc in Computer Science, University of Greenwich, United Kingdom
Postgraduate training
- MSc in Artificial Intelligence, City University of Macau, London, United Kingdom