The ENBIS 2027 conference offers a rich and engaging scientific programme, bringing together experts from academia and industry to discuss current challenges, methodological advances, and impactful applications of statistics and data science. The programme is designed to foster exchange, collaboration, and inspiration across disciplines and sectors.
ENBIS-27 Keynote Speakers
The conference will feature keynote lectures delivered by leading experts, combining invited international speakers and distinguished ENBIS award recipients.
Invited Keynote Speakers
- Our first confirmed invited keynote speaker is Prof. Veronica Bowman OBE, who will deliver her lecture on Friday, 3 September 2027.
- Prof. Veronica Bowman OBE (PhD, CMath, FIMA, CDMP) is an internationally recognised data and digital leader with a track record of delivering high-impact analytical capabilities across government and industry. She is a statistician and modeller specialising in Bayesian inference, uncertainty quantification, and their application to decision-making, digital twins, and modelling architectures. She was awarded an OBE in the 2022 New Year Honours for developing CrystalCast, a system that used uncertainty analysis and Bayesian inference to estimate disease transmission during the COVID-19 pandemic.
She spent much of her career translating academic mathematical research into operational capability at the Defence Science and Technology Laboratory. A desire to apply these approaches to a broader range of societal and environmental challenges led her to an environmental start-up and subsequently to Frazer-Nash, where she is now a Principal Consultant. She continues to work at the intersection of advanced mathematics and decision-making, with a particular focus on applying mathematical methods to engineering, environmental, and climate-related challenges.
Her work spans national pandemic modelling, including the development of methods for combining epidemiological models and communicating uncertainty to policy-makers, as well as wider applications of data science across energy, defence, health, engineering and emerging industrial systems.
Titles and abstracts for all keynote lectures will be progressively announced.