Mr Abdullah Saqib

(he/him)

Research

My research lies at the intersection of neuroscience, artificial intelligence (AI), and computational modelling, with a particular focus on memory consolidation, attention, and predictive coding. I am especially interested in how we can use techniques from machine learning and statistics to better understand the mechanisms of cognition during sleep and wakefulness, and how these insights can inform the development of more adaptive and human-like AI systems.

Current Projects

Targeted Memory Reactivation (TMR) and REM Sleep

As a Research Assistant in the Sleep Lab at Cardiff University, supervised by Dr Penelope Lewis, I am currently investigating how Targeted Memory Reactivation (TMR) during REM sleep influences memory consolidation. We use a serial reaction time task paired with emotional cueing, followed by sleep recordings to examine the reactivation of task-related memories.

This project also involves applying machine learning classifiers to EEG data in order to detect neural signatures of memory reactivation. The aim is to establish whether classifiers trained on wake data can generalise to predict TMR-related activity during sleep.

Past Projects

Neuro-behavioural Modelling and Predictive Coding

Previously, at the University of Sussex, I developed a neuro-behavioural model combining predictive processing and hierarchical Gaussian filters to explore individual differences in attention and decision-making. This work is part of a broader effort to bridge Bayesian theories of brain function with data-driven approaches in AI.

Cognitive Social System Modelling

In a separate project at Sussex, I developed a Cognitive Social System framework that combines reflexivity theory and cognitive social structures to model perception and action in embedded social agents. This agent-based system was optimised using a microbial genetic algorithm, enabling adaptive learning in dynamic social networks. This line of work contributes to understanding social cognition, agent-based modelling, and emergent behaviour in human and artificial collectives.

Broader Themes

My long-term goal is to contribute to the development of neuro-inspired AI systems and computational tools that can analyse complex behavioural and neural data. I aim to understand how attentional dynamics, emotion, and memory systems interact across timescales and states (e.g. sleep vs wake), and how these processes may differ across individuals.

Keywords: Targeted Memory Reactivation, REM Sleep, EEG, Machine Learning, Predictive Coding, Hierarchical Gaussian Filters, Attention, Memory Consolidation, Neuro-AI, Social Cognition, Agent-Based Modelling, Computational Neuroscience

Biography

I am currently a Research Assistant at the Sleep Lab at Cardiff University, supervised by Dr Penelope Lewis. My research focuses on Targeted Memory Reactivation (TMR) during REM sleep, using emotional cueing and a serial reaction time task to examine whether memory consolidation can be enhanced. I also apply machine learning classifiers to EEG data to investigate neural correlates of memory reactivation.

Previously, I completed a Master of Science in Artificial Intelligence and Adaptive Systems at the University of Sussex, graduating with distinction. My MSc thesis explored individual differences in attentional processing under a predictive coding framework using behavioural data. During this time, I also gained experience with computational neuroscience, probabilistic models, and neuro-behavioural modelling.

Before transitioning to neuroscience and AI, I worked as a Data Scientist at Healthequity.ai, where I analysed UK healthcare inequalities using supervised and unsupervised machine learning algorithms and public healthcare datasets. My work integrated NHS datasets and received recognition at a Cambridge research event.

I previously completed a Bachelor of Arts in Economics and Statistics at the University of British Columbia (UBC), Canada. There, I developed strong quantitative and analytical skills, which later informed my transition into neuroscience and artificial intelligence.

Honours and awards

• Gold Spirit Award, University of Sussex

• Engineering and Informatics Award, University of Sussex 

• International Student Scholarship, University of British Columbia 

• Outstanding International Student Award, University of British Columbia 

Professional memberships

• Asia Pacific Next Generation Fellow, Japan (2024 – Present)

• President, Consciousness Society, University of Sussex (2024)