Ben Lambert
Associate Professor of Statistics and AI in Science
I am a mathematician and a statistician with a strong interest in biological systems, and I develop computational methods that help to uncover biological and epidemiological knowledge. Most of my work tends to be in vector-borne systems, such as those for mosquito-borne diseases.
I direct Oxford's Schmidt AI in Science programmes: our Postdoctoral Fellowship programme, and our Visiting Faculty programme for Fellows from India and Africa. Both of these schemes provide funding for Fellows who apply methods from AI to advance scientific knowledge, and these schemes will collectively fund 164 Fellow-years of research by 2030.
Recent publications
Misspecification of the generation time distribution and its impact on Rt estimates in structured populations
Journal article
Bouros I. et al, (2026), Journal of Theoretical Biology, 632, 112536 - 112536
MetaBeeAI: An AI pipeline for structured evidence extraction from biological literature
Journal article
Parkinson RH. et al, (2026), Ecological Informatics, 96, 103813 - 103813
A Bayesian modelling framework for inference of latent infection risk patterns from virus neutralisation assay titration data
Preprint
Alrefae TA. et al, (2026)
Evolution and spillover dynamics of yellow fever at the forest-urban interface in Brazil.
Journal article
Telles-de-Deus J. et al, (2026), Nature microbiology, 11, 877 - 891
MetaBeeAI: an AI pipeline for structured evidence extraction from biological literature
Preprint
Parkinson RH. et al, (2025)