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 in the unit SEB113 - Quantitative Methods in Science.

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.

Occasionally, I blog about my research and you can find more about my publication history at QUT eprints and Google Scholar. Occasionally I publish useful code, including a package for tidying MCMC output from coda or rjags entitled mmcc, and a package to bring some of the common linear model diagnostics like variance inflation factors and tables of confidence intervals to GAMs from mgcv in mgcv.helper.

A selected list of publications is shown below, indicating recent projects I’ve been involved with and key papers I’ve written. A full list of publications is available here.


From 2016 I have been employed as a Postdoctoral Fellow at the QUT node of the ARC Centre of Excellence for Mathematical and Statistical Frontiers, working on a variety of environmental statistics problems such as coral cover in the Great Barrier Reef and jaguar conservation in Peru.


I am working with colleagues at QUT and QIMR to investigate the replication and spread of Dengue fever.

Great Barrier Reef

The Monitoring Through Many Eyes project is a collaboration between scientists, data analysts and marine explorers, working together to document, analyse and predict the health of the Great Barrier Reef. The aim is to tap into the power of Citizen Scientists by collating thousands of underwater images take by recreational divers and snorkelers on the Reef each year.

Citation Description
Vercelloni et al. (2017) Gathering information from experts and citizen scientists in a virtual environment to understand what people believe makes an aesthetically pleasing reef


The world needs new ways to do conservation. There is no time for endangered animals and their environments. We need an evidence base to make informed decisions, and we need it now. We are addressing this problem by combining traditional conservation with virtual reality technology, mathematical and statistical modelling, local knowledge and international expertise.

Through our Many Eyes on the Wild program, we aim to facilitate faster, better decisions about management and monitoring. We are developing and using these approaches to help conserve jaguars in the Peruvian Amazon.

Citation Description
Mengersen et al. (2017) Spatial modelling of presence only data with a variety of statistical and machine learning techniques
Bednarz et al. (2016) Using virtual environments to elicit information about ecosystems

Spike sorting

I am currently working on simulation studies for two papers with a former ACEMS PhD student, Dr Zoé van Havre, where we are looking at finite and infinite mixture modelling methods for classifying action potential data from EEG scans.

Citation Description
van Havre et al. (2017) Overfitted mixtures and Dirichlet process mixtures for spike classification

ECR Retreat

As an early career researcher (ECR) at ACEMS I helped organise the ECR Retreat as part of the November 2017 ACEMS retreat. The ECR retreat used a blend of talks and UnConference style collaborative sessions to foster collaboration between the ECRs at the various nodes and to make ourselves known and avaialble to the ACEMS PhD students.


Since 2013 I have been involved in the development and delivery of SEB113 - Quantitative Methods for Science as part of the ST01 Bachelor of Science course at Queensland University of Technology. The course covers a variety of mathematical and statistical topics taught through scientific case studies and makes use of the R language for all computation.

In 2015, the teaching team was the recipient of the Vice Chancellor’s Performance Award for innovation in redesiging the unit for student success through encouraging engagement with multiple technologies.

Citation Description
Czaplinski et al. (2016) Redesign of a first year unit with blended learning to improve student engagement and success


Between 2009 and 2013 I was a PhD student at the International Laboratory for Air Quality and Health (ILAQH) under the supervision of Professors Lidia Morawska and Kerrie Mengersen and Dr Sama Low Choy.

Between 2013 and 2015 I was employed as a Postdoctoral Fellow at ILAQH to support the research being done across a variety of topics in air quality. The bulk of my postdoctoral work at ILAQH was related to the UPTECH project. The project seeks to determine the effect of the exposure to airborne nano and ultrafine (UF) particles emitted from motor vehicles on the health of children in schools.

I still collaborate with colleagues at ILAQH on a variety of topics including occupational exposure, child health, atmospheric processes, exposure assessment, and instrumentation.

Spatial modelling

Citation Description
M. M. Rahman, Yeganeh, et al. (2017) Land use regression modelling with variable selection of NO\(_\mathrm{x}\) and NO\(_2\) concentrations
M. M. Rahman, Mazaheri, et al. (2017) Bayesian GAMs used to model urban background particle concentrations and the contribution of new particle formation
Yeganeh et al. (2017) Application of statistical and machine learning models used to estimate air pollution concentrations from satellite imagery

Atmospheric processes

Citation Description
Salimi et al. (2017) New particle formation typically occurs during daylight; here we investigate evidence of night time events
Jayaratne, Clifford, and Morawska (2015) Predictive model for whether or not midday new particle formation events will occur based on morning PM\(_{10}\) and visibility

Exposure and health effects

Citation Description
Clifford et al. (submitted) Main UPTECH paper detailing the inflammatory and pulmonary response to ultrafine particles
Morawska et al. (2017) Indoor sources of exposure in the home, office, school and aged care facilities
Salthammer et al. (2016) Impact of climate and air pollution on children’s health at school
Toms et al. (2015) Multinomial regression modelling to look at the relative proportions of various polybrominated diphenyl ethers across classrooms
Clifford et al. (2014) Mathematical and statistical models for particle deposition inside the lung
Mazaheri et al. (2014) Analysis of inhaled particles in primary school children


Citation Description
Rivas et al. (2017) Identification of problems with DustTrak performance seen during measurement campaigns – indicating conditions under which this instrument shouldn’t be used
Stevanovic et al. (2015) Semi-parametric regression used to model particle losses in aerosol measuring equipment


Thesis outputs

Citation Description
Clifford (2013) Spatio-temporal modelling of ultrafine particle number concentration - Using the Generalised Additive Model to model temporal trends in ultrafine particle number concentration with penalised splines and spatial trends with Gaussian Markov Random fields.
Falk et al. (2015) Review paper on modern statistical methods for analysing spatial data
Clifford, Low Choy, et al. (2013) Spatio-temporal model in INLA of air pollution in Brisbane, Australia
Clifford and Low Choy (2012) A book chapter on various implementations of Bayesian spline regression
Clifford et al. (2012) A preprint of an unpublished paper looking into Bayesian GAMs with autocorrelated errors
Clifford et al. (2011) Using GAMs to model temporal trends and covariate effects for PNC in Helsinki, Finland
Clifford (2008) Honours thesis on dispersion of a compount in shear-augmented flow

Conference items

Citation Description
Clifford et al. (2015) A missing data model for estimating cigarette exposure from survey data and partially complete blood tests
Mazaheri, Clifford, and Morawska (2015) Comparing two methods of exposure assessment
Morawska et al. (2014) Synthesis of indoor air pollution results from UPTECH study
Clifford, Mazaheri, et al. (2013) Mathematical and statistical models for particle deposition inside the lung


Bednarz, Tomasz, June Kim, Ross Brown, Allan James, Kevin Burrage, Sam Clifford, Jacqueline Davis, et al. 2016. “Virtual Reality for Conservation.” In Proceedings of the 21st International Conference on Web3d Technology, 177–78. ACM. doi:10.1145/2945292.2945319.

Clifford, S., M. Mazaheri, B. Yeganeh, K. Mengersen, G. Marks, and L. Morawska. 2015. “Uncertainty in Exposure Estimates and Imputation of Missing Aerosol Data in an Epidemiological Study.” Poster – European Aerosol Conference.

Clifford, Sam. 2008. “An Analysis of Shear-Augmented Dispersion with Analytical and Numerical Methods.” Honours Thesis, School of Mathematical Sciences, Queensland University of Technology.

———. 2013. “Spatio-Temporal Modelling of Ultrafine Particle Number Concentration.” Doctoral Thesis, School of Chemistry, Physics; Mechanical Engineering, Queensland University of Technology.

Clifford, Sam, and Sama Low Choy. 2012. “Case Studies in Bayesian Statistical Modelling and Analysis.” In, edited by Clair Alston and Kerrie Mengersen, 197–220. Wiley Series in Probability and Statistics. Wiley.

Clifford, Sam, Sama Low Choy, Tareq Hussein, Kerrie Mengersen, and Lidia Morawska. 2011. “Using the Generalised Additive Model to Model the Particle Number Count of Ultrafine Particles.” Atmospheric Environment 45 (32): 5934–45. doi:10.1016/j.atmosenv.2011.05.004.

Clifford, Sam, Sama Low Choy, Mandana Mazaheri, Farhad Salimi, Kerrie Mengersen, and Lidia Morawska. 2013. “A Bayesian Spatio-Temporal Model of Panel Design Data: Particle Number Concentration in Brisbane, Australia.” ArXiv, no. 1206.3833 (february).

Clifford, Sam, Mandana Mazaheri, E. R. Jayaratne, M. A. Megat Mokhtar, F. Fuoco, G. Buonanno, and L. Morawska. 2013. “Estimation of Inhaled Ultrafine Particle Surface Area Dose in Urban Environments.” Australian Mathematical Society (Australian; New Zealand Industrian; Applied Mathematics).

———. 2014. “Estimation of Inhaled Ultrafine Particle Surface Area Dose in Urban Environments.” ANZIAM Journal 55: C437–C447. doi:10.21914/anziamj.v55i0.7819.

Clifford, Sam, Mandana Mazaheri, Farhad Salimi, Wafaa Nabil Ezz, Bijan Yeganeh, Samantha Low Choy, Katy Walker, Kerrie Mengersen, Guy B. Marks, and Lidia Morawska. submitted. “Effects of Exposure to Ambient Ultrafine Particles on Respiratory Health and Systemic Inflammation in Children.” Environmental Health Perspectives.

Clifford, Sam, Bjarke Mølgaard, Jukka Corander, Kaarle Hämeri, Sama Low Choy, Kerrie Mengersen, and Tareq Hussein. 2012. “Bayesian Semi-Parametric Forecasting of Particle Number Concentration: Penalised Splines and Autoregressive Errors.” ArXiv, no. 1207.0558 (september).

Czaplinski, Iwona, Sam Clifford, Ruth Luscombe, and Brett Fyfield. 2016. “A Blended Learning Model for First Year Science Student Engagement with Mathematics and Statistics.”

Falk, M. G., C. L. Alston, C. A. McGrory, S. Clifford, E. A. Heron, D. Leonte, M. Moores, C. D. Walsh, A. N. Pettitt, and K. L. Mengersen. 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.

Jayaratne, E. R., S. Clifford, and L. Morawska. 2015. “Atmospheric Visibility and PM\(_{10}\) as Indicators of New Particle Formation in an Urban Environment.” Environmental Science & Technology 49 (21): 12751–7. doi:10.1021/acs.est.5b01851.

Mazaheri, M., S. Clifford, and L. Morawska. 2015. “Inhaled Particle Surface Area Dose: Stationary Vs Personal Monitoring.” Poster – European Aerosol Conference.

Mazaheri, Mandana, Sam Clifford, Rohan Jayaratne, Megat Azman Megat Mokhtar, Fernanda Fuoco, Giorgio Buonanno, and Lidia Morawska. 2014. “School Children’s Personal Exposure to Ultrafine Particles in the Urban Environment.” Environmental Science and Technology 48 (1): 113–20. doi:10.1021/es403721w.

Mengersen, Kerrie, Erin E. Peterson, Samuel Clifford, Nan Ye, June Kim, Tomasz Bednarz, Ross Brown, et al. 2017. “Modelling Imperfect Presence Data Obtained by Citizen Science.” Environmetrics 28 (5). Wiley. doi:10.1002/env.2446/.

Morawska, L., G.A. Ayoko, G.N. Bae, G. Buonanno, C.Y.H. Chao, S. Clifford, S.C. Fu, et al. 2017. “Airborne Particles in Indoor Environment of Homes, Schools, Offices and Aged Care Facilities: The Main Routes of Exposure.” Environment International 108 (Supplement C): 75–83. doi:10.1016/j.envint.2017.07.025.

Morawska, L., M. Mazaheri, S. Clifford, F. Salimi, R. Laiman, and L Crilley. 2014. “Indoor Air Pollution Sources and Exposures in Primary Schools: UPTECH Synthesis .” In Indoor Air. Hong Kong.

Rahman, M. M., Mandana Mazaheri, Sam Clifford, and Lidia Morawska. 2017. “Estimate of Main Local Sources to Ambient Ultrafine Particle Number Concentrations in an Urban Area.” Atmospheric Research 194. Elsevier: 178–89. doi:10.1016/j.atmosres.2017.04.036.

Rahman, M. M., Bijan Yeganeh, Sam Clifford, Luke Knibbs, and Lidia Morawska. 2017. “Development of a Land Use Regression Model for Daily NO\(_2\) and NO\(_x\) Concentrations in the Brisbane metropolitan area, Australia.” Environmental Modelling and Software 95: 168–79. doi:10.1016/j.envsoft.2017.06.029.

Rivas, Ioar, Mandana Mazaheri, Mar Viana, Teresa Moreno, Samuel Clifford, Congrong He, Oliver F Bischof, et al. 2017. “Identification of Technical Problems Affecting Performance of Dusttrak Drx Aerosol Monitors.” Science of The Total Environment 584. Elsevier: 849–55. doi:10.1016/j.scitotenv.2017.01.129.

Salimi, Farhad, Md Rahman, Sam Clifford, Zoran Ristovski, Lidia Morawska, and others. 2017. “Nocturnal New Particle Formation Events in Urban Environments.” Atmospheric Chemistry and Physics 17 (1). Copernicus GmbH: 521–30. doi:10.5194/acp-17-521-2017.

Salthammer, Tunga, Erik Uhde, Tobias Schripp, Alexandra Schieweck, Lidia Morawska, Mandana Mazaheri, Sam Clifford, et al. 2016. “Children’s Well-Being at Schools: Impact of Climatic Conditions and Air Pollution.” Environment International 94. Pergamon: 196–210. doi:10.1016/j.envint.2016.05.009.

Stevanovic, S., B. Miljevic, P. Madl, S. Clifford, and Z. Ristovski. 2015. “Characterisation of a Commercially Available Thermodenuder and Diffusion Drier for Ultrafine Particles Losses.” Aerosol and Air Quality Research 15 (1): 357–63. doi:10.4209/aaqr.2013.12.0355.

Toms, L., M. Mazaheri, S. Brommer, S. Clifford, D. Drage, J. Mueller, P. Thai, S. Harrad, L. Morawska, and F. Harden. 2015. “Brominated Flame Retardants in Primary Schools: Sources and Exposures.” Environmental Research 142: 135–40. doi:10.1016/j.envres.2015.06.007.

van Havre, Zoé, Nicole White, Judith Rousseau, Sam Clifford, and Kerrie Mengersen. 2017. “Clustering Action Potential Spikes: Insights on the Use of Overfitted Finite Mixture Models and Dirichlet Process Mixture Models.” Australia and New Zealand Journal of Statistics under review.

Vercelloni, Julie, Sam Clifford, Alan R Pearse, Ross Brown, Allan James, Bryce Christensen, Tomasz Bednarz, et al. 2017. “Understanding Aesthetic Attributes of Coral-Reefs: Using Virtual Reality to Support Conservation of Ecosystem Services.” Conservation Letters submitted.

Yeganeh, Bijan, Michael G Hewson, Samuel Clifford, Luke D Knibbs, and Lidia Morawska. 2017. “A Satellite-Based Model for Estimating PM\(_{2.5}\) Concentration in a Sparsely Populated Environment Using Soft Computing Techniques.” Environmental Modelling & Software 88. Elsevier: 84–92. doi:10.1016/j.envsoft.2016.11.017.