PhD Research    

I am working on developing Bayesian approaches to modelling behaviour under two distinct, but complementary, contexts:

1. Responses to internal perturbations  i.e., investigation of mechanisms that support functional recovery post–brain damage,
2. Responses to external perturbations  i.e., investigating readjustment of behaviour in volatile settings 

Through this, we have developed a quantitative framework to evaluate degenerate architectures [Sajid, Parr, et al, Cerebral Cortex, 2020], and measure the distinct routes through which functional recovery might manifest in damaged brains [ Sajid, Holmes, et al, Scientific Reports, 2021]. Furthermore, my work provides us with a formal understanding of the mechanisms crucial for building adaptive agents equipped with flexible (i.e., degenerate) but efficient neuronal architectures i.e., an appropriate stability-plasticity trade-off [Sajid, Convertino, et al, In prep]. Separately, my work has established the relevance of having appropriate planning strategies to evince adaptive behaviour [Sajid, Ball, et al, Neural Computation, 2021]

I have benefitted from research internships at Huawei (Neuromorphic Computing group; Zafeirios Fountas), Zebra Technologies (Machine Learning group; Biswa Sengupta) and Harvard University (Computational Cognitive Neuroscience Lab; Samuel Gershman).