Current Teaching

Analysing empirical information is the cornerstone of many domains, including science, engineering, economics and social science. Graduates in these domains must be able to process, manipulate and present the growing quantities of data effectively. Although computing should play a key role, we rarely exploit the full power of existing or custom software to efficiently convert data into information and then knowledge. INFO1903 was designed to equip students with the skills and techniques for exploiting data effectively.

  • COMP5046 Statistical Natural Language Processing

This unit deals with techniques for the automatic processing of natural languages (such as English, French, etc) and the engineering of such software systems. Engineering processes will be described in the context of methods for creating effective tools for information retrieval and extraction, question answering, classifying and clustering of the documents in a large corpora. Processing sub-systems for such tasks as tokenisation, lexical verification, part-of-speech tagging, parsing and word sense disambiguation will be described. Particular emphasis is given to methods that analyse the meaning in texts and the general application of machine learning methods to these topics.

A couple of posters about our online programming system Δ used in ENGG1801 and INFO1903 and research led teaching in INFO1903 Δ.

I am currently completing the Graduate Certificate in Educational Studies (Higher Education).

Previous Teaching

  • ENGG1801 Engineering Computing