Dr Ken Kitson
Data Analytics (Undergraduate)
This module focuses on the range of approaches, methodologies, techniques and tools for data analysis, and the use of data analysis findings to inform decision-making in an industrial / business context.
Data Analytics (Postgraduate)
This module focuses on the range of approaches, methodologies, techniques and tools for data analysis, and the use of data analysis findings to inform decision-making in an industrial / business context. It exposes students to a range of industry-standard statistical and data analysis techniques and tools, and fosters awareness of the challenges associated with working with large datasets. The module also covers topics related to the legal, social, ethical and professional issues associated with data storage and analysis. Students will undertake practical work including empirical data analysis and summarisation / presentation of the results to a range of relevant stakeholders.
My broad research interest is causal discovery, that is machine learning algorithms which infer cause and effect relationships from data. The algorithms I am interested in produce a Bayesian Network (BN) which is a probabilistic graphic model which comprises a graph which indicates which variables are causes of which other variables, and parameters which define the form and strength of these relationships.
My proposed Ph.D. topic is Improving Causal Discovery using Active Learning - that is, where the algorithm itself identifies and requests knowledge from a human expert which the algorithm determines would be most beneficial in improving the accuracy of the BN graph.
Constantinou AC, Liu Y, Chobtham K et al. (2021). Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data..
Kitson NK, Constantinou AC (2021). Learning Bayesian networks from demographic and health survey data..