Currently I lead the Machine Learning team at the Wellcome Trust, where we develop machine learning models and metrics to support Wellcome fund new discoveries in life, health, and wellbeing. We also support the Wellcome Collection, a museum that explores the connections between medicine, life and art.

Areas I have worked on at Wellcome (working with many fantastic colleagues, teams and external collaborators) include:

Leadership: Since joining Wellcome in 2022 I've implemented development standards, a robust prioritisation process and a technical road map, increasing the delivery of high impact machine learning products and the status of data science within the organisation. Improving our data and MLOps infrastructure alongside setting the direction of the teams technical work. The teams work includes the automatic topic modelling of research publications using BERTopic and the Llama large language model, development of WellcomeBertMesh a transformer model for tagging texts with MeSH terms, using text content and network dynamics to predict translational potential, and the development of network and citation based metrics. You can follow our team's work on the Wellcome Data blog here.

Wellcome Academic Graph: Designed, modelled and developed the Wellcome Academic Graph, a heterogeneous academic graph stored in Neo4j. Capturing over 2 billion relationships between 200 million academic entities, enabling our work to apply and development network based metrics and geometric machine learning.

I am always interested in discussing the use of data and machine learning in research funding and data science for public good.