Research Grant
[Cite as https://purl.org/au-research/grants/arc/DE160100741]Researchers: Professor Chris Drovandi (Discovery Early Career Researcher Award)
Brief description Tractable Bayesian algorithms for intractable Bayesian problems. This project seeks to develop computationally efficient and scalable Bayesian algorithms to estimate the parameters of complex models and ensure inferences drawn from the models can be trusted. Bayesian parameter estimation and model validation procedures are currently computationally intractable for many complex models of interest in science and technology. These include biological processes such as the efficacy of heart disease, wound healing and skin cancer treatments. Potential outcomes of the project include new algorithms to significantly economise computations and improved understanding of the mechanisms of experimental data generation. Improved models of wound healing, skin cancer growth and heart physiology supported by these algorithms could improve population health.
Funding Amount $382,274
Funding Scheme Discovery Early Career Researcher Award
- ARC : DE160100741
- PURL : https://purl.org/au-research/grants/arc/DE160100741
