Twelfth Annual Conference of the Australasian Bayesian Network Modelling Society (ABNMS2020)
· Conference Program
· Workshop Program
· Key Dates
· Code of Conduct
December 2-3 & 11, 2020 : Workshops
December 9-10, 2020 : Conference
We are excited to announce that we will be hosting our first ABNMS Virtual Conference. The online meeting is free of cost to attend for members, but registration is required (payment is needed if membership needs renewal). The meeting will take place on Zoom. Registrants must agree to adhere to the code of conduct and meeting rules. Please feel free to contact us if you have any questions.
We are inviting members and conference attendees to submit a topic for the panel discussion. Submit your topic here.
Prof Tom Snelling is director of the Health and Clinical Analytics team in the School of Public Health at the University of Sydney, and an infectious diseases physician in the Sydney Children's Hospital Network. Tom is pioneering in the application of Bayesian approaches to the design, coordination, implementation and analysis of public interest studies, and is successfully leading a suite of multi-institutional collaborative learning health projects across Australia. Working with a range of collaborative research groups across diverse clinical domain areas, these include Bayesian adaptive studies to improve the treatment and prevention of severe gastroenteritis in remote Aboriginal children, the primary prevention of food allergies in children, SMS text messages to improve timeliness of routine immunisation, the management of cystic fibrosis and, more recently, Bayesian network models for the diagnosis, prognosis and management of COVID-19.
Dr Steven Mascaro is a co-director of Bayesian Intelligence, a consulting company that specialises in Bayesian network research and applications, and also a research fellow at Monash University. Steven has worked on a variety of Bayesian network projects, starting in 2006 with a BN-based poker playing bot developed at Monash. Since then, he has been involved in the development of both Bayesian network models and software, including elicited and machine learned models, in domains covering ecology, defence (including anomaly detection, situation awareness, intelligence analysis and future technology assessment), biosecurity (including surveillance planning and pest risk analyses), fire risk management, rail maintenance and infectious diseases. He is currently working on causal models of COVID-19 pathogenesis to assist prognosis and diagnosis.
Partners & Sponsors
ABNMS would like to gratefully acknowledge our conference partners and sponsors: