James is the Chief Technologies Officer (CTO) at a Machine Learning Consultancy called Filament; a role that he carries out part-time, whilst also studying for his doctorate as a member of the EPSRC CDT in Urban Science. He has won the BCS prize for best final year undergraduate project for his work on Partridge, a software pipeline for automating information extraction from scientific literature. His research interests include Natural Language Processing techniques, Neural Networks and information extraction.
80% of all data today is unstructured. This includes news articles, research reports, social media posts and enterprise systems data. IBM Watson, which James was a Systems Architect for, is a technology platform that uses natural language processing and machine learning to reveal insights from large amounts of unstructured data. At the heart of the Watson system are more than 200 million pages of structured and unstructured content; Watson is also able to connect to the Internet as a further source of data. Watson's applications range from education to healthcare, and there are numerous applications in the context of urban science, ranging from the analysis of municipal documents, the assessment of policy, early warning public health, to the identification of data-driven insights from the federated search of real-time urban data. James is continuing to apply this knowledge in his new CTO role and as a research scientist at WISC.
Alignment with EPSRC research themes: Artificial intelligence technologies; Built environment; Complexity science; Human communication in ICT; ICT networks and distributed systems; Natural language processing; Mobile computing; Pervasive and ubiquitous computing; Sensors and instrumentation.
For more information on James' research, please see his online Portfolio.
Poster detailing James research.