With an increasing reliance on data, not only in evidence-based policy-making, but as the fuel for a proliferation of systems using Artificial Intelligence (AI) being used in society, a wide range of skills encompassing the entire data life-cycle are required to build and deploy these systems, including, for example: managing data collection and storage at scale, using information extraction, machine learning and natural language processing,  performing statistical analyses and testing, visualising and reporting on data, along with general software skills, problem solving ability and a flexible approach to overcoming challenges as they arise.

Research in large-scale content analysis requires a good working knowledge of all of these aforementioned areas to identify the underlying patterns, trends and relationships in data and understand them.

On these topics, I have been working on the following directions: