Dr Sam Clifford
Research Fellow
I’m a statistician working at Queensland University of Technology on a range of environmental and environmental health problems such as jaguar conservation, reef conservation, and air pollution and its health impacts. In addition, I teach mathematics and statistics to first year science students.
My undergrad was in applied and computational mathematics, focussing on fluid dynamics in my honours year. Over time, I drifted towards Bayesian statistical modelling, where I use semi-parametric regression and hierarchical modelling for spatial, temporal, and spatio-temporal modelling.
Between 2010 and 2013 I was a PhD student at ILAQH under the supervision of Professors Lidia Morawska and Kerrie Mengersen and Dr Sama Low Choy. After graduating, I was employed as a Postdoctoral Fellow at ILAQH to support the research being done across a variety of topics in air quality. I still collaborate with my former colleagues on a variety of topics including occupational exposure, child health, atmospheric processes, exposure assessment, and instrumentation.
Research Interests:
Bayesian statistics
Maths education
Modelling of biological and environmental systems
Semiparametric regression modelling
Spatio-temporal models
Qualifications:
PhD
Bachelor of Applied Science (Honours) in Mathematics
Projects
Publications
Invited talks, refereed proceedings and other conference outputs
(2016). Bayesian Approaches in Occupational Health Surveillance.
International Society for Bayesian Analysis.
(2016). Virtual reality for conservation.
International Conference on Web3D Technology. 177–178. doi: 10.1145/2945292.2945319
(2016). Virtual reality for conservation.
Web3D 2016: 21st International Conference on Web3D Technology. 177–178. doi: 10.1145/2945292.2945319
Journal Articles
(2018). Influence of Spatial Aggregation on Prediction Accuracy of Green Vegetation Using Boosted Regression Trees.
Remote Sensing. 10(8), 1260. doi: 10.3390/rs10081260
(2017). Using Boosted Regression Trees and Remotely Sensed Data to Drive Decision-Making.
Open Journal of Statistics. 07(05), 859 - 875. doi: 10.4236/ojs.2017.75061
(2017). Nocturnal new particle formation events in urban environments.
Atmospheric Chemistry and Physics. 17(1), 521 - 530. doi: 10.5194/acp-17-521-2017
(2017). Airborne particles in indoor environment of homes, schools, offices and aged care facilities: The main routes of exposure.
Environment International. 108, 75 - 83. doi: 10.1016/j.envint.2017.07.025
(2017). A satellite-based model for estimating PM 2.5 concentration in a sparsely populated environment using soft computing techniques.
Environmental Modelling & Software. 88, 84 - 92. doi: 10.1016/j.envsoft.2016.11.017
(2017). Modelling imperfect presence data obtained by citizen science.
Environmetrics. 28(5), e2446. doi: 10.1002/env.2446
(2017). Identification of technical problems affecting performance of DustTrak DRX aerosol monitors.
Science of The Total Environment. 584-585, 849 - 855. doi: 10.1016/j.scitotenv.2017.01.129
(2017). Development of a land use regression model for daily NO 2 and NO x concentrations in the Brisbane metropolitan area, Australia.
Environmental Modelling & Software. 95, 168 - 179. doi: 10.1016/j.envsoft.2017.06.029
(2017). Estimate of main local sources to ambient ultrafine particle number concentrations in an urban area.
Atmospheric Research. 194, 178 - 189. doi: 10.1016/j.atmosres.2017.04.036
(2015). Recent Bayesian approaches for spatial analysis of 2-D images with application to environmental modelling.
Environmental and Ecological Statistics. 22(3), 571-600. doi: 10.1007/s10651-015-0311-1
Research links
