Find a Data Champion

Ali is Senior Data Scientist and public-health/transport modeller in the Public Health Modelling (PHM) group at the MRC-Epidemiology Unit, University of Cambridge. He is interested in active travel, specifically cycling research. 

Coming from a Computer Science background, with a focus on modelling in his PhD, for over a decade, he has been doing data-driven research and development. This includes Exploratory Data Analysis (EDA), Statistical Modelling (or Machine Learning), Interactive Visualization, all with a focus on collaborative, transparent and reproducible research. In addition, he leads in project management and managing, training, guiding, and teaching of junior staff in his Unit. His work can be seen on GitHub at https://github.com/usr110.

Elizabeth has an MPhil in HPS from Cambridge and has worked for the Newton Project Canada. She has worked for the Darwin Correspondence Project for more than fifteen years, and assisted in the conversion of the Project's core files to TEI XML, and is now developing and implementing strategies to ensure the quality, robustness, interoperability, and long-term viability of our electronic data. She is a co-founder of Epsilon, a nineteenth century science letters platform and has been a guest lecturer at the Digital Humanities at Oxford Summer School.

I'm a research fellow working to improve data management practices broadly across the materials and chemical sciences, with the aim to accelerate discovery and enable new data-driven approaches in the physical sciences. I lead the development of the decentralised open source RDM platform, datalab, used by several labs in Cambridge and beyond to track sample provenance, ingest raw characterisation data from instruments and easily disseminate data within and between labs. datalab has been designed primarily with materials chemistry and battery groups in mind, but has been extended to work for polymer research, direct air capture and autonomous labs. I also work extensively on API standardisation for crystal structure databases, via my involvement in OPTIMADE. I am very happy to discuss how people can engage with this work if they are in this domain, or how the approach could be adopted by other domains.

Before starting my current role, I completed my undergraduate studies in Theoretical Physics at the University of Manchester, after which I joined the University of Cambridge for an MPhil in Scientific Computing and subsequent PhD in Physics where I worked on crystal structure prediction for battery materials. I then joined UCLouvain in Belgium for a postdoc and research fellowship, before making my way back to Cambridge in 2025 as a Leverhulme Trust Early Career Research Fellow.