Broadly, the themes underlying my research, supervised by Prof. David Lagnado, include the role of causal models in reasoning and decision-making under uncertainty. My PhD will focus on exploring how people make inferences and decisions from uncertain evidence and how these compare to normative Bayesian models. Through this line of research, I aim to identify novel features and biases in human inference as well as develop methods to mitigate the effect of these biases on judgment accuracy. I will also investigate people’s information search strategies compared to normative information-gain models. This work will extend to the domains of legal decision-making, intelligence analysis and forensic investigations.
My PhD is funded by the Intelligence Advanced Research Projects Activity (IARPA), USA. As such, I am a member of the Bayesian ARgumentation via Delphi (BARD) project team, working on improving reasoning in intelligence analysts through a tool that uses Causal Bayesian Networks as underlying structured representations for argument analysis.
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