I study learning and decision making. Much of my research looks at simple decision making, and simple skill learning, using measures of behaviour informed by work done in computational theory, robotics and neuroscience. More recently a strand of my research looks at complex decisions, and bias in decision making, and what might be called ‘evidence-informed persuasion’.
Three core ambitions of my research are:
- Data Intensive Methods – robust, scalable, reproducible experiments and analysis which are transparent, sharable and work as well with 400,000 data points as they do with 40.
- Interdisciplinarity – collaborating across all scholarly fields.
- Public Engagement – listening to public interests, sharing research process and outcomes with non-specialists, giving back to the publics involved with research.