Current Research Interest Φ Symbolic Machine Learning especially Inductive Logic Programming Φ Applications of Symbolic Machine Learning and ILP to real-world problems In particular, to problems in computational biology including the identification of miRNAs, qualitative models of biological systems, and toxicology models for drug-design The analysis of text, specifically to do with the construction of relational attributes from semi-structured text Φ Implementation of ILP In particular, the ILP systems Aleph and P-Progol Incorporation of probabilistic optimisation techniques for scalabilit Techniques for combination with other learning methods (for example, deep neural networks) Φ Conceptual development of ILP Application of optimal search theory The use of designed experiments for hyper-parameter optimisation