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Extending the applicability and explainability of machine learning algorithms for decision making

   Business School

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  Dr Bin Liu, Dr Matthew Revie  Applications accepted all year round  Self-Funded PhD Students Only

About the Project


Machine learning algorithms have attracted considerable attention for prediction and decision-making in various industries. When used for decision-making, it is vital to determine the interpretability of machine learning algorithms.

Project details

This PhD project aims to develop and deploy novel machine learning algorithms to produce interpretable solutions for decision-making problems. The project will explore how to incorporate domain knowledge into the machine learning algorithm and evaluate the uncertainty associated with the prediction algorithm for decision-making.


Students should have (or expect to have) a Bachelor or Master Degree (overall score 65 or above) in Management Science, Computer science, Mathematics and Statistics, Operations Research or other related subjects. Desirable skills in programming, data analytics, optimisation, although not essential.

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