Dear all,
The 3rd BioInference conference (https://bioinference.github.io/2024/) is taking place at the University of Warwick on 5th-7th June 2024.
Launched in 2022, BioInference aims to bring together researchers from across statistics and mathematical modelling who work with biological systems, and from all career stages, to foster discussions between the two communities and to prompt collaborations.
If you would like to attend the event in-person, please sign up by the 26th May 2024 (tickets limited and on a first come first served basis) at
https://warwick.ac.uk/fac/sci/statistics/news/bioinference2024/registration/
Note that the registration is considered complete and successful only after having paid the £70 registration fee (covering all coffee breaks, lunch breaks, wine and food reception on the 6th June 2024).
The conference will consist of contributed talks and poster sessions, with more than 20 poster presentations. The programme and the full list of contributed talks, poster presentations and the two day schedule can be found at
https://warwick.ac.uk/fac/sci/statistics/news/bioinference2024/programme/
with the book of abstract available here.
A list of confirmed talks includes:
* Hannah Bensoussane (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 Filippi (Imperial College London) - Variational Bayes for high-dimensional proportional hazard models
* Guglielmo Gattiglio (University of Warwick) - Nearest Neighbor GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers
* Hong Ge (University of Cambridge) - TBC
* Andonis Gerardos (AMU) - MiSFI, a robust algorithm to select a minimal model for dynamical data with large sampling intervals
* Petar Jovanovski (Chalmers University of Technology and University of Gothenburg) - Towards Data-Conditional Simulation for ABC Inference in Stochastic Differential Equations
* Cathal Mills (University of Oxford) - A multi-disciplinary approach for wavelet analysis, climate- based modelling, and probabilistic ensemble forecasting of dengue epidemic dynamics
* Hamid Rahkooy (University of Oxford) - Algebraic identifiability of partial differential equation models
* Nicolas Rubido (University of Aberdeen) - Small-worldness favours network inference in synthetic neural networks
* Heba Sailem (King’s College London) - Deep learning approaches for identifying predictive biomarkers from the tumour microenvironment.
* Vahid Shahrezaei (Imperial College London) - Bayesian model discovery for revers-engineering biochemical networks from data
* Catalina Vallejos (University of Edinburgh) - Using routine healthcare data to predict future health
* Andrea Mario Vergani (Human Technopole & Politecnico di Milano) - Prediction of incident cardiovascular events using cardiac MRI-derived latent factors
* Qiquan Wang (Imperial College London) - A Topological Gaussian Mixture Model for Bone Marrow Morphology in Leukaemia
* Huizi Zhang (University of Edinburgh) - Bayesian modelling of RNA velocity from single-cell RNA sequencing data
We are looking forward to seeing you at BioInference 2024.
Best wishes,
Massimiliano on the behalf of the BioInference Committee
Enrico Bibbona (Politecnico di Torino); Ioana Bouros (Oxford); Julia Brettschneider (Warwick); Raiha Browning (Warwick); Fergus Cooper (Oxford); Marina Evangelou (Imperial College London); Aden Forrow (Maine); Constandina Koki (Warwick); Ben Lambert (Oxford); Chon Lok Lei (Macau); Massimiliano Tamborrino(Warwick); Tom Thorne (Surrey); Yongchao Huang (Aberdeen).
