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Smarter Experiments for the Lab of the Future: Man and Machine Knowledge Integration

Unilever employ experienced people and have large repositories of historic experimental data. This project relates to combining the information inherent in these contexts to help optimise decisions about which experiments to conduct in the future. More specifically, this project will develop tools to support such decision-making.

Mature techniques can solve parts of this problem. Indeed, psychologists have developed structured thinking techniques to help mitigate cognitive biases when capturing human expertise. Similarly, data scientists have developed statistical methods for analysing data. However, there is relatively little research that is genuinely at the interface between these two disciplines and which attempts to synergise the views held by the two communities of academic researchers.

Through careful statistical modelling of the process of asking questions of experts, together with analysis of the psychology of using interface to state-of-the-art data science, this project seeks to develop decision support tools that explicitly pull on both psychology and data science.


I'm part of the Data Science and Signal Processing and Expertise and Decision Making research groups. I'm also a member of the Evaluation of Techniques for Uncertainty Representation Working Group (ETURWG) and Open Source Tracking and Estimation Working Group (OSTEWG) of the International Society for Information Fusion (ISIF).

Recent Projects