Benedetto de Martino

Professor of Cognitive Neuroscience at UCL and director of the Brain Decision Modelling Laboratory

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Leading figure in the interdisciplinary field of Neuroeconomics
Researched the neural basis of human cognitive biases at Caltech and Cambridge University
Published an extensive review into how human decision-making compares with AI

Benedetto De Martino is a Professor of Cognitive Neuroscience at University College London, where he directs the Brain Decision Modelling Laboratory.

He is one of the leading figures in the interdisciplinary field of Neuroeconomics, a new research area that combines techniques from neuroscience with theoretical models from economics and computational neuroscience.

His work has been acknowledged by leading figures in economics. Daniel Kahneman, the Nobel Prize winner in Economics in 2002, commented that his work on the neural basis of the framing effect ‘confirms that serious theorising in the domains of judgement and decision-making can be informed by imaging results and that the integration of concepts from both lines of research is necessary and feasible’.

Benedetto completed his PhD at University College London, where he began to study the neural basis of human cognitive biases. In 2008, he was awarded a Wellcome postdoctoral fellowship with Professor Daniel Kahneman as a mentor. In the following years, he worked in the Department of Economics at the California Institute of Technology (Caltech) with Professor Colin Camerer, a leading behavioural economist. During this period, he published influential papers, including one that showed that financial bubbles can be triggered by the inflation of value representations due to social interaction and theory of mind.

In 2014, he was awarded a Sir Henry Dale Fellowship from the Royal Society and the Wellcome Trust, basing his research group at Cambridge University. In 2016, he moved to the Institute of Cognitive Neuroscience, where, with his group, he began to study how human decision-making compares with decisions made by artificial intelligence agents. In 2017, he received a Google Faculty Research Award to pursue this research agenda. He has developed these ideas, drawing parallels with work in AI, in an extensive review ‘Goals, Usefulness, and Abstraction in Value-based Choice,’ published in in Trends in Cognitive Neuroscience.

His work has been published in the most important scientific journals, including Science, Nature Neuroscience, Nature Human Behaviour, Neuron, eLife, and he has been invited to present his work at the main universities around the world (both to Economics and Neuroscience Departments) and in international conferences and symposia.

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