Emily‘s work involves building data collection, cleaning, and analysis tools for use in technical and research projects. She is currently attached to two EU projects relating to pandemic response.
The aim of STAMINA (H2020) is to develop social media and web analytics tools to support evidence-driven decision making in response to a pandemic crisis.
Emily is also contributing to the COVINFORM project (H2020), that aims to develop risk assessment models to measure the impact of the SARS-nCoV-2 (COVID-19), with a particular focus on vulnerable groups.
Emily‘s interests lie in applying machine learning techniques to gain insights into the complex phenomena that arise at the interface between human and natural systems (so-called ‘cybernetic’ systems). She is especially interested in explicit inclusion of diverse perspectives to ensure the social inclusivity of data-driven technologies.
Emily holds a PhD in Statistical Physics and an MSc in Complex Systems Science from the University of Warwick, and an MPhys in Physics from the University of Manchester. She wrote her PhD thesis on models of feedback and control for stochastic thermodynamics. Before joining Trilateral Research, Emily lived and worked in Kyoto, Japan as a researcher and teacher. She also holds a postgraduate diploma in education.