Emma Byrne holds a PhD in Computer Science from University College London. Her research interests broadly cover the area of artificial intelligence. The two main strands of her research are learning from data with logical formalisms and evolutionary computation.
She is currently a researcher at Middlesex University on the CABot project. Her main role is to study models of vision in a biologically inspired neural architecture.
She is also a consulting researcher at the school of Primary Care and Population Sciences at University College London, where she is applying Argumentation to the evaluation of the NHS "Connecting for Health" IT project.
Her recent research activities include: the development of a framework to identify interesting news that is logically inconsistent with expectations concerning the behaviour of entities in the real world (PhD work, supervised by Dr Anthony Hunter); a logical framework for template creation and information extraction (with colleagues from the Bioinformatics group at University College London); analysis through Argumentation of the policymaking process in an NHS Primary Care Trust (with the UCL Evidence Science Group); and the development of a Multi-Objective Genetic Algorithm optimiser for experiment flow with the Robot Scientist group at Aberystwyth University (formerly University of Wales, Aberystwyth).