All talks will be held in room MS.01 in the Zeeman BuildingLink opens in a new window (Mathematics). The Registration and coffee breaks on Thursday will be held on "The Street", in front of MS.01. All lunches, poster session, wine and food reception, and Friday coffee break will be held on "The Atrium" in the Statistics BuildingLink opens in a new window. A schedule of the main conference is reported below. All abstracts are available here.

List of talks:

• Hannah BensoussaneLink opens in a new window (University of Warwick) - Bayesian individual-level infectious disease modelling: heterogeneous transmission and dealing with costly likelihood evaluation when estimating missing data

• Alex Browning (University of Oxford) - "Little data" in mathematical oncology

• Helena Coggan (University College London) - An agent-based modelling framework to study cell plasticity in non-small cell lung cancer

• Sarah FilippiLink opens in a new window (Imperial College London) - Variational Bayes for high-dimensional proportional hazard models.

• Guglielmo GattiglioLink opens in a new window (University of Warwick) - Nearest Neighbor GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers.

• Hong GeLink opens in a new window (University of Cambridge) - TBC

• Andonis GerardosLink opens in a new window (AMU) - MiSFI, a robust algorithm to select a minimal model for dynamical data with large sampling intervals.

• Cathal MillsLink opens in a new window (University of Oxford) - A multi-disciplinary approach for wavelet analysis, climate- based modelling, and probabilistic ensemble forecasting of dengue epidemic dynamics

• Hamid RahkooyLink opens in a new window (University of Oxford) -Algebraic identifiability of partial differential equation models

• Heba SailemLink opens in a new window (King’s College London) - Deep learning approaches for identifying predictive biomarkers from the tumour microenvironment.

• Catalina VallejosLink opens in a new window (University of Edinburgh) - Using routine healthcare data to predict future health

• Huizi Zhang (University of Edinburgh) - Bayesian modelling of RNA velocity from single-cell RNA sequencing data

List of lightnining talks - Thursday, 12-1pm

• Petar JovanovskiLink opens in a new window (Chalmers University of Technology and University of Gothenburg) - Towards Data-Conditional Simulation for ABC Inference in Stochastic Differential Equations.

• Giorgos MinasLink opens in a new window (University of St Andrews) - Inference for large non-linear stochastic systems

• Nicolas RubidoLink opens in a new window (University of Aberdeen) - Small-worldness favours network inference in synthetic neural networks.

• Vahid ShahrezaeiLink opens in a new window (Imperial College London) - Bayesian model discovery for revers-engineering biochemical networks from data.

• Andrea Mario VerganiLink opens in a new window (Human Technopole & Politecnico di Milano) - Prediction of incident cardiovascular events using cardiac MRI-derived latent factors.

• Adriana ZancaLink opens in a new window (University of Melbourne) - Inferring heterochrony in craniofacial development.

List of Poster contributors:

• Tarek Alrefae (University of Oxford) - Heterogeneity in Models of Infectious Disease.
• Jake CarsonLink opens in a new window (University of Warwick) - Inference of Infection Disease Transmission through a Relaxed Bottleneck Using Multiple Genomes per host.
• Yu ChenLink opens in a new window (Imperial College London) - Bayesian rate consistency model to uncovering the hidden structure of contemporary sexual networks in Africa
• Luca Del CoreLink opens in a new window (University of Nottingham) - Accounting for stochastic gating whilst estimating ion channel kinetics from whole-cell patch-clamp recordings.
• Richard EverittLink opens in a new window (University of Warwick) - Ensemble Kalman inversion approximate Bayesian computation.
• Alicia GillLink opens in a new window (University of Warwick) - Bayesian Inference of Reproduction Number from Epidemic and Genomic Data using MCMC Methods.
• Laura Guzman-RinconLink opens in a new window (University of Warwick) Statistical framework for the nowcasting and forecasting of infectious disease growth rates
• Andrii KrutsyloLink opens in a new window (Institute of Computer Science Polish Academy of Science) - The Forward-Forward Algorithm: Biologically Inspired Optimization for Continual Learning.
• Alessia MapelliLink opens in a new window (Politecnico di Milano) -Graphs for representation of interacting biological systems and prediction of complex diseases.
• Thomas Morrish (University of Warwick) - An approximate likelihood framework motivated by the irregular movement of animals.
• Michael PlankLink opens in a new window (University of Canterbury) - A compartment-based model of Covid-19 in New Zealand: exploiting model structure to improve inference methods.
• Ian RobertsLink opens in a new window (University of Warwick) - Bayesian Inference for the Structured Coalescent.
• Kristian RomanoLink opens in a new window (University of Warwick) Hidden Markov Models for Real Time Telemetric Monitoring of the Circadian Rhythm.
• Elena Sabbioni Link opens in a new window(Politecnico di Torino) Regularized MANOVA test for zero-inflated semicontinuous high-dimensional data
• Joseph ShuttleworthLink opens in a new window (University of Nottingham) - Using many different protocols to characterise discrepancy in mathematical ion channel models.
• Nenad ŠuvakLink opens in a new window (University of Osijek) - Time-changed SIRV model for epidemic of SARS-CoV-2 virus.
• Jia Le Tan Link opens in a new window(University of Warwick) - Pareto Smoothed Sequential Monte Carlo.
• Joseph Lok Hei TsuiLink opens in a new window (University of Oxford) - Optimal disease surveillance with graph-based active learning.
• João Pedro Valeriano MirandaLink opens in a new window (CINAM, Aix-Marseille Université) - Recovering the dynamics of unobserved quantities in stochastic processes.
• Sarah VollertLink opens in a new window (Queensland University of Technology) - Constructing constraint-informed prior distributions for inference in data-limited scenarios: a case study in ecosystem population models
• Mengxin Xi (King's College London) - Extrapolation methods for Bayesian Inverse Problems
• Dominic ZhouLink opens in a new window (University of Warwick) - Adaptive MCMC inference in the Kingman coalescent model – propriety, ergodicity, efficiency.