Statistical Machine Learning with Applications in Industrial Processes (in cooperation with Tata Steel)

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Recent innovations in machine learning has been largely driven by the emergence of Big Data that are correlated, high-dimensional, dynamic and often not in the Euclidean space. The PhD project is aimed at developing novel statistical machine learning methodology andalgorithms to address the modelling challenges that arise. The project is motivated by the need for building predictive models to understand steel manufacturing processes. Currently we are exploring possible applications of network science, looking for a new generative network model that incorporates covariate information.