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
MetaBeeAI: an AI pipeline for full-text systematic reviews in biology
Preprint
Parkinson RH. et al, (2025)
Asymmetric limits on timely interventions from noisy epidemic data
Journal article
Parag KV. et al, (2025), Communications Physics, 8
Real-time inference of the end of an outbreak: Temporally aggregated disease incidence data and under-reporting
Journal article
Ogi-Gittins I. et al, (2025), Infectious Disease Modelling, 10, 935 - 945
Mixing methods: How listening to researchers, healthcare workers, and community members can improve the design of studies testing medical innovations for Neglected Tropical Diseases.
Journal article
Erber AC. et al, (2025), PLoS neglected tropical diseases, 19
Modelling the effects of adult emergence on the surveillance and age distribution of medically important mosquitoes.
Journal article
Stopard IJ. et al, (2025), PLoS computational biology, 21