Skip to main content
Welcome to the ACEMS Reportal
All contributors should enter data on all of the Centre’s reportable key performance indicators (KPIs).
Menu
About Us
Contact Us
Annual Reports
2021 Annual Report
2020 Annual Report
2019 Annual Report
2018 Annual Report
2017 Annual Report
2016 Annual Report
2015 Annual Report
2014 Annual Report
Opportunities at ACEMS
Vacancies
Scholarships
Sponsorship opportunities
Equity and Diversity
Code of Conduct
Carer's Provision Fund
Equity and Diversity Resources
People
Directorate
Chief Investigators
Research Fellows
Associate Investigators
Students
Professional Staff
Affiliate Members
Committees
Governance Advisory Board
Scientific Advisory Committee
Equity and Diversity Committee
Past Members of ACEMS
Research
COVID-19 Research & Resources
Challenging data
Multiscale models
Enabling Algorithms
Informed decisions
Publications
Research Briefs
ACEMS Technical Talks
Collaborate
Start a collaboration
Industry Projects
Industry Affiliate Programme
Mentoring @ ACEMS
Partners
Support Schemes for ACEMS Members
News and Events
Podcast: The Random Sample
News from ACEMS
Media Stories
Events
ACEMS 2021 Final Retreat
Women in Maths Day 2021
Newsletters
Contact the ACEMS media team
Outreach and Education
Mathscraft
Book: Data Science & Machine Learning
Spotlight on Women in Maths
ACEMS Public Lecture Series
Games
Member Portal
Home
People
Past Members of ACEMS
Brenda Vo
Dr Brenda Vo
PhD Student
Queensland University of Technology
Research Interests:
Agent-based models
Applied statistics
Approximate Bayesian Computation
Bayesian inference
Bayesian statistical modelling
Qualifications:
PhD
Publications
Invited talks, refereed proceedings and other conference outputs
2016
Vo, B.
,
Drovandi C. C.
,
Pettet G.
, &
Pettitt A.N.
(2016).
Approximate Bayesian Computation for cell biology.
Sixth IMS-ISBA Joint Meeting Bayes Comp at MCMski 5.
Journal Articles
2015
Vo, B.
,
Drovandi C. C.
,
Pettitt A.N.
,
Pettet G.
, & Byrne H.
(2015).
Melanoma Cell Colony Expansion Parameters Revealed by Approximate Bayesian Computation.
PLoS Computational Biology. 11
(12),
doi:
10.1371/journal.pcbi.1004635
Vo, B.
,
Drovandi C. C.
,
Pettitt A.N.
, & Simpson M. J.
(2015).
Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation.
Mathematical Biosciences. 263,
133-142.
doi:
10.1016/j.mbs.2015.02.010
Research links
ORCID
Home
People
Past Members of ACEMS
Brenda Vo
Privacy
Contact Us
Copyright © 2014-2024
