IMPORTANT WARNING: Phishing! Note that ill-intentioned people may be trying to contact some of participants by email or phone to get money and personal details, by pretending to be part of the staff of our conference center (CIRM). CIRM and the organizers will NEVER contact you by phone on this issue and will NEVER ask you to pay for accommodation/ board / possible registration fee in advance. Any due payment will be taken onsite at CIRM during your stay.
Bayesian methods are now firmly established in the fields of Statistics and Machine Learning and are being increasingly applied to “Big Data”. However, there are still gaps in knowledge about the theory, methodology, computation and application of Bayesian methods in this context.
This conference will bring together an international and interdisciplinary group of researchers and practitioners to share insights, research, challenges and opportunities in developing and using Bayesian statistics in the Big Data era. The anticipated outcomes include: knowledge transfer, new collaborative networks, new research directions and new statistical tools to address challenging problems in the real world.
The program will include oral presentations and substantial time for discussion after each presentation, as well as poster presentations with specific sessions for presentation and discussion.
The program will also include dedicated time for research discussion, collaboration and networking. Sessions on topics such as career pathways and mentoring will be scheduled for postgraduates and early career researchers.
To pre-register for this event, please click on the blue "Apply here" button at the top of the page.
Please note that registration for this event is free but participants will have to cover all other expenses including travel, lodging and meals.
(Prices of board and lodging at CIRM are available here: https://www.cirm-math.com/prices.html )
There is a maximum number of participants so registrations will be received on a first come, first served basis.
The organisers reserve the right to refuse participants if necessary.