Kevin Kermani Nejad
Neural & machine learning group
I am interested in understanding the computations performed by neocortical microcircuits. Specifically, my research focuses on how superficial and deep neocortical layers jointly learn a model of the world in a self-supervised way. My current project aims to develop a self-supervised model of neocortical microcircuit that explains neural activity in superficial and deep layers in visuomotor tasks. I complement this line of research with work on biologically plausible models of self-supervised multimodal learning and curiosity-based reinforcement learning.
I completed my undergraduate degree in Computer Science at King’s College London and a MSc in Computational Applied Mathematics at the University of Edinburgh.
[w/ Paul Anastasiades]