Dr Marius Golubickis

Research Overview

Broadly, my research could be categorised as computational social cognition. It is a novel and increasingly influential approach that studies the computational mechanisms underpinning social biases during information processing (e.g., decision-making, attention, learning).

My research focuses primarily on the extent and origin of self-bias (e.g., biases for self-relevant information). I also have an active line of investigation exploring issues in person perception, specifically the processes that underpin stereotype-based information processing.

My work often challenges conventional discipline-specific approaches by combining well-established methodologies from social cognition, cognitive psychology, and the vision sciences to explore how various social aspects, such as self-relevance and stereotypical beliefs, guide decision-making. In addition, I utilise specialised computational modelling techniques (e.g., Drift Diffusion Modelling and its variants) to explicate the psychological processes that underpin task performance.