2023 Conference

In 2022, we organised the inaugural Bioinference conference, with a primary goal to bring together researchers from all career stages across statistics and mathematical modelling who work with biological systems to foster discussions between the two communities and to prompt collaborations: the talks are available via our public YouTube channel.

The feedback we received from the participants was overwhelmingly positive: all those who gave feedback scored us 8/10 and above when asked whether they would recommend the conference to others.

On 8th-9th June 2023, we are holding the 2nd Bioinference conference at the Pitt Rivers Museum at the University of Oxford. In doing so, we hope to build a community of mathematical biologists and statisticians, facilitating dialogue and collaborations between these two groups across career stages. You can sign up for the in-person event here and for the online event here.

This year’s conference is organised by: Ioana Bouros (Oxford); Fergus Cooper (Oxford); Richard Creswell (Oxford); Aden Forrow (Maine); David Gavaghan (Oxford); Ben Lambert (Exeter); Chon Lok Lei (Macau); Massimiliano Tamborrino (Warwick); Tom Thorne (Surrey).

The conference is generously sponsored by:

• The Doctoral Training Centre, University of Oxford
• The Department of Computer Science, University of Oxford
• The European Society for Mathematical and Theoretical Biology

Schedule #

Thursday 8th June #

Friday 9th June #

Poster presentations

• Enrico Bibbona, Politecnico di Torino, “Estimating the ratio between the contagiousness of two viral strains”
• Julia Brettschneider, University of Warwick, “Microscopic images and infections counts from a point process perspective”
• Austin Brown, University of Warwick, “Geometric ergodicity of Gibbs samplers for Bayesian error-in-variable regression”
• Alexander Browning, University of Oxford, “Modelling heterogenity with random parameters”
• Raiha Browning, University of Warwick, “AMISforInfectiousDiseases: an R package to fit a transmission model to a prevalence map”
• Viktoria Brunner, University of Oxford, “Large-scale Identification of Compensatory Mutations in the RNA Polymerase of Mycobacterium tuberculosis”
• Alice Corbella, University of Warwick, “Inference of the case fatality risk at the beginning of an epidemic: a state-space model perspective and a robust particle filter”
• Molly Cui, Kings College London, “Bayesian modelling and sequential learning of latent epidemic dynamics”
• Lloyd Chapman, Lancaster University, “Bayesian inference for spatiotemporal individual-level epidemic models”
• Alicia Gill, University of Warwick, “Bayesian inference of reproduction number from genomic and epidemic data using particle MCMC”
• Adam Howes, Imperial College London, “Fast approximate Bayesian inference for small-area estimation of HIV indicators using the Naomi model”
• Owen Jones, Cardiff University, “Estimating the virulence of managed parasite populations”
• Arnau Quera-Bofarull, University of Oxford, “Bayesian calibration of differentiable simulators”
• Lutecia Servius, King’s College London, “Comparing classification methods and their generalisability on antibody repertoire”
• Maria Veretennikova, University of Oxford, “Circadian clock analysis for precision medicine”
• Hiu Ching Yip, Politecnico di Torino, “Modelling lemurs’ calls with nearest neighbour Gaussian process”
• Reza Taheri, University of Turin, “Using Generalized Lagrange Chebyshev collocation method in order to solve the shortest path problems”