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Researcher into how we understand causation wins Society award

12 April 2018

Dr Neil Bramley has won the Society’s Award for Outstanding Doctoral Research Contributions to Psychology.

His doctoral work, completed in the Department of Experimental Psychology at University College London, examined how people learn about the causal structure of the world. It had a special emphasis on the way adults and children combine intervention, observation and temporal information to build up their causal models piece by piece. 
Dr Bramley has introduced new ideas and approaches to the study of causal cognition in both theory and methodology. His work combines careful experimentation with sophisticated mathematical and computational modelling.  He has pioneered the use of information-based analyses of intervention strategies, and has linked sampling techniques from machine learning to psychological processes underpinning belief change and action choice.
Having already achieved an impressive number of refereed publications, he is now a Moore-Sloan post-doctoral associate in the Centre for Data Science at New York University.
Dr Bramley said:
“I am delighted and deeply grateful to the British Psychologicial Society for this award.  Thanks to my supervisors David Lagnado and Peter Dayan, parents Alison and Glen, and my girlfriend Paula for putting up with me through the PhD years.  I am now enjoying building on this work with a bunch of collaborators around the US and Europe, so stay tuned.”
Nicola Gale, the President of the Society, said:
“We are delighted to recognise Dr Bramley’s achievements and wish him the best for his developing career.”
The Society makes this award annually, and our Awards Committee bases its judgement on published articles carried out for a doctorate.
Two articles submitted in support of Dr Bramley’s nomination were:
Bramley, N.R., Lagnado, D.A. & Speekenbrink, M. (2015). Conservative forgetful scholars: How people learn causal structure through sequences of interventions. Journal of Experimental Psychology: Learning, Memory and Cognition, 41, 707-731.
Bramley, N.R., Dayan, P., Griffiths, T.L. & Lagnado, D.A. (2017). Formalizing Neurath’s ship: Approximate algorithms for online causal learning. Psychological Review 124(3), 301


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