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Personal profile


Ajaz Bhat is a senior research associate with Larissa Samuelson and John Spencer in Developmental Dynamics Lab at UEA. He is working on the interaction between language development, visual attention and memory. In particular, his research is trying to ascertain if children can make sense of information spread across their different interactions with the environment and what brain mechanisms could underlie such abilities. Ajaz uses a range of methods such as computational modelling and eye-tracking experiments with children to demystify such brain processes and connect what kids learn to what they see or vice versa.

Ajaz holds a doctorate from the Italian Institute of Technology where he designed a brain-like memory system for robots to learn and reason in a developmental fashion. His PhD work also showed how such developmental learning systems can be applied in industry for online learning of new tasks. Prior to his doctoral studies, he completed a masters in computing from Kashmir, the vale he hails from. His main interests are in computational intelligence: what makes human minds so unique and are there computational explanations to our uniqueness?

Key Research Interests

Humans (and many non-human animals) are apt at learning cumulatively and exploiting experiences prospectively to generate goal-directed behaviours with flexibility and creativity. Understanding the computational processes in brains that give rise to cognitive behaviours and endowing artificial agents (robots) with such brain-like mechanisms to enable them to act cognitively like (and alongside) natural agents, form the long-term goals of my research.
Broadly, my research interests lie in computational modelling of word learning, concept formation, motor control, skill acquisition, causal inference, constructive memory-based reasoning, and computational creativity.
At UEA, I investigate interactions between language development, novelty, visual attention and memory. In particular, my research explores how children make sense of the noisy information they are exposed to in daily interactions with the environment. How is learning modulated by attention and memory processes, and what neurocomputational mechanisms underlie these cross-situational learning behaviours? I use neurodynamical systems modelling and eye-tracking experiments with children and adults to demystify these behaviours.


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