I am a Lecturer (Assistant Professor) in Machine Learning based at the School of Informatics within The University of Edinburgh. I also hold a Royal Academy of Engineering Research Fellowship on verifiable and robust meta-learning. I was previously a postdoc with Prof Timothy Hospedales, and a PhD student with Prof Bernhard Pfahringer.
I have a particular interest in developing and leveraging theoretical advances to improve how machine learning is done in practice. I am interested in applying machine learning to a variety of application domains, including signal processing, computer vision, natural language processing, robotics, and data mining. My current research is focused on developing machine learning systems that can seek out and/or leverage extra contextual information about the tasks to be solved, thus enabling one to learn more robust models with less data. Such contextual information could include examples of good models for related tasks, natural language descriptions of the phenomena being modelled, knowledge of underlying causal mechanisms, or other meta-data associated with tasks.