Dr Jacinta Holloway-Brown
PhD Student, Research Associate
Dr Jacinta Holloway Brown is a Postdoctoral Fellow in the QUT School of Mathematical Sciences and Centre for Environment. She develops new statistical machine learning methods to solve environmental and sustainable development problems. Her research currently focuses on developing new Bayesian experimental design approaches for modelling biodiversity and using remote sensing analysis to monitor change in forests.
In her previously role as a research associate in ACEMS, Jacinta has developed and taught hands on workshops on machine learning methods for analysing satellite imagery data for the United Nations, and run these workshops in Bogota, Colombia and Bangkok, Thailand. Previously, she worked for the Australian Bureau of Statistics for years, more recently in methodology and tourism statistics roles.
Research Interests:
Applied statistics
Machine Learning
Machine Learning methods for Big Data
Satellite image analysis
Spatial statistics
Sustainable Development Goals
Qualifications:
Grad Dip(Applied Statistics) (Swinburne Institute of Technology)
Bachelor of Business (Economics)/Journalism (Queensland University of Technology)
Projects
Publications
Invited talks, refereed proceedings and other conference outputs
(2020). Propagating uncertainty through to model forecasts: deterministic Lotka-Volterra systems as a case study.
Quantitative Ecology Virtual Meeting 2020.
(2019). Beta distributions and random forest for better forest monitoring.
Bayes on the Beach 2019.
(2019). Environmental Data in the Development of SDG indicators.
62nd ISI World Statistics Congress.
(2018). Spatial and machine learning methods of satellite imagery analysis for Sustainable Development Goals.
IAOS-OECD Better Statistics for Better Lives.
Journal Articles
(2018). Statistical Machine Learning Methods and Remote Sensing for Sustainable Development Goals: A Review.
Remote Sensing. 10(9), 1365. doi: 10.3390/rs10091365
