Associate Professor Andrew Zammit Mangion

Associate Professor Andrew Zammit Mangion

Associate Professor

01.2012 PhD awarded from the University of Sheffield, UK, titled Modelling from spatio-temporal data: A systems perspective.

09.2007 B.Eng. (Hons.) awarded from the University of Malta in Electrical Engineering.

Science
School of Mathematics & Statistics

I am an Associate Professor in the School of Mathematics and Statistics at the University of New South Wales, and an Honorary Associate Professor with the School of Mathematics and Applied Statistics at the University of Wollongong. My research sits at the intersection of statistics, computation, and the environmental sciences, with a focus on developing and applying spatio-temporal models to understand complex environmental systems.

I completed my PhD at the University of Sheffield between 2008 and 2011, where I developed variational Bayesian methods for approximate inference in spatio-temporal log-Gaussian Cox process models. This work contributed to early scalable inference methods for complex point process models and was successfully applied to problems in conflict modelling.

Following a brief postdoctoral appointment at the University of Edinburgh, I held an academic position at the University of Bristol from 2012 to 2014, before joining the University of Wollongong in 2014. I joined the University of New South Wales in 2026. Across these roles, my work has combined methodological development, large-scale computation, and interdisciplinary collaboration, particularly in environmental and climate science.

  • Books | 2019
    Wikle CK; Zammit-Mangion A; Cressie N, 2019, SPATIO-TEMPORAL STATISTICS WITH R, http://dx.doi.org/10.1201/9781351769723
    Books | 2013
    Zammit-Mangion A; Dewar M; Kadirkamanathan V; Flesken A; Sanguinetti G, 2013, Modeling conflict dynamics with spatio-temporal data, http://dx.doi.org/10.1007/978-3-319-01038-0
  • Book Chapters | 2023
    Gopalan G; Zammit-Mangion A; McCormack F, 2023, 'A Review of Bayesian Modelling in Glaciology', in Statistical Modeling Using Bayesian Latent Gaussian Models with Applications in Geophysics and Environmental Sciences, pp. 81 - 107, http://dx.doi.org/10.1007/978-3-031-39791-2_2
  • Journal articles | 2026
    Stephens BB; Jin Y; Sweeney C; McKain K; Gaubert B; Baker DF; Basu S; Bertolacci M; Chevallier F; Commane R; Crowell S; Deng F; Johnson MS; Keeling RF; Liu J; Liu Z; Maity S; Morgan EJ; Patra P; Philip S; Wofsy SC; Zammit-Mangion A, 2026, 'Improved latitudinal carbon budgets from global airborne surveys', Proceedings of the National Academy of Sciences of the United States of America, 123, http://dx.doi.org/10.1073/pnas.2523984123
    Journal articles | 2026
    Valderrama-Giraldo J; Liu Q; Bertolacci M; Bransby F; Watson P; Zammit-Mangion A, 2026, 'Comparison of Approaches to Data-Driven Site Characterization in an Offshore Carbonate Soil Environment in North Western Australia', ASCE ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering, 12, http://dx.doi.org/10.1061/AJRUA6.RUENG-1679
    Journal articles | 2026
    Vercelloni J; Logan M; Zammit-Mangion A; Sainsbury-Dale M; Schaffelke B; Mengersen K; González-Rivero M, 2026, 'Predicting Coral Cover Trends From Local to Broad Spatial Scales', Global Change Biology, 32, http://dx.doi.org/10.1111/gcb.70998
    Journal articles | 2026
    Vu BA; Gunawan D; Zammit-Mangion A, 2026, 'Recursive variational Gaussian approximation with the Whittle likelihood for linear non-Gaussian state space models', Computational Statistics and Data Analysis, 218, http://dx.doi.org/10.1016/j.csda.2025.108324
    Journal articles | 2026
    de Kreij R; Zammit-Mangion A; Rayson M; Jones N; Zulberti A, 2026, 'Statistical Inversion of Sea Surface Temperature to Predict Submesoscale Near-Surface Ocean Currents', Journal of Advances in Modeling Earth Systems, 18, http://dx.doi.org/10.1029/2025MS005424
    Journal articles | 2025
    Bertolacci M; Zammit-Mangion A; Valderrama Giraldo J; O’Neill M; Bransby F; Watson P, 2025, 'GeoWarp: Warped Spatial Processes for Inferring Subsea Sediment Properties', Journal of the American Statistical Association, 120, pp. 710 - 722, http://dx.doi.org/10.1080/01621459.2024.2445874
    Journal articles | 2025
    Huser R; Zammit-Mangion A, 2025, 'Raphaël Huser and Andrew Zammit-Mangion's contribution to the Discussion of the 'Discussion Meeting on the Analysis of citizen science data', Journal of the Royal Statistical Society Series A Statistics in Society, 188, pp. 714 - 716, http://dx.doi.org/10.1093/jrsssa/qnaf010
    Journal articles | 2025
    Huser R; Zammit-Mangion A, 2025, 'Raphaël Huser and Andrew Zammit-Mangion’s contribution to the Discussion of the ‘Discussion Meeting on the Analysis of citizen science data’', Journal of the Royal Statistical Society Series A Statistics in Society, 188, pp. 714 - 716, http://dx.doi.org/10.1093/jrsssa/qnaf012
    Journal articles | 2025
    Jacobson J; Bertolacci M; Zammit-Mangion A; Schuh A; Cressie N, 2025, 'WOMBAT v2.S: A Bayesian Inversion Framework for Attributing Global CO2 Flux Components From Multiprocess Data', Environmetrics, 36, http://dx.doi.org/10.1002/env.70052
    Journal articles | 2025
    Sainsbury-Dale M; Zammit-Mangion A; Richards J; Huser R, 2025, 'Neural Bayes Estimators for Irregular Spatial Data Using Graph Neural Networks', Journal of Computational and Graphical Statistics, 34, pp. 1153 - 1168, http://dx.doi.org/10.1080/10618600.2024.2433671
    Journal articles | 2025
    Vu Q; Moores MT; Zammit-Mangion A, 2025, 'Warped Gradient-Enhanced Gaussian Process Surrogate Models for Exponential Family Likelihoods with Intractable Normalizing Constants', Bayesian Analysis, 20, pp. 435 - 459, http://dx.doi.org/10.1214/23-BA1400
    Journal articles | 2025
    Zammit-Mangion A; Sainsbury-Dale M; Huser R, 2025, 'Neural Methods for Amortized Inference', Annual Review of Statistics and Its Application, 12, pp. 311 - 335, http://dx.doi.org/10.1146/annurev-statistics-112723-034123
    Journal articles | 2025
    Zheng X; Cressie N; Clarke DA; McGeoch MA; Zammit-Mangion A, 2025, 'Spatial-statistical downscaling with uncertainty quantification in biodiversity modelling', Methods in Ecology and Evolution, 16, pp. 837 - 853, http://dx.doi.org/10.1111/2041-210X.14505
    Journal articles | 2024
    Bertolacci M; Zammit-Mangion A; Schuh A; Bukosa B; Fisher JA; Cao Y; Kaushik A; Cressie N, 2024, 'INFERRING CHANGES TO THE GLOBAL CARBON CYCLE WITH WOMBAT V2.0, A HIERARCHICAL FLUX-INVERSION FRAMEWORK', Annals of Applied Statistics, 18, pp. 303 - 327, http://dx.doi.org/10.1214/23-AOAS1790
    Journal articles | 2024
    Mackintosh A; McCormack F; Jones R; Purich A; Beckmann J; Tielidze L; Saunderson D; Macha J; Rand C; Bird L; Strugnell J; Lau S; Smith J; McNeil M; Whitmore R; McLennan S; Fulop R; Zammit Mangion A; Henley B; McGregor H, 2024, 'Securing Antarctica’s Environmental Future: the East Antarctic Ice Sheet ', , http://dx.doi.org/10.5194/egusphere-egu24-12985
    Journal articles | 2024
    Ng TLJ; Zammit-Mangion A, 2024, 'Mixture modeling with normalizing flows for spherical density estimation', Advances in Data Analysis and Classification, 18, pp. 103 - 120, http://dx.doi.org/10.1007/s11634-023-00561-7
    Journal articles | 2024
    Richards J; Sainsbury-Dale M; Zammit-Mangion A; Huser R, 2024, 'Neural Bayes estimators for censored inference with peaks-over-threshold models', Journal of Machine Learning Research, 25
    Journal articles | 2024
    Sainsbury-Dale M; Zammit- Mangion A; Cressie N, 2024, 'Modeling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data Using FRK', Journal of Statistical Software, 108, pp. 1 - 39, http://dx.doi.org/10.18637/jss.v108.i10
    Journal articles | 2024
    Sainsbury-Dale M; Zammit-Mangion A; Huser R, 2024, 'Likelihood-Free Parameter Estimation with Neural Bayes Estimators', American Statistician, 78, pp. 1 - 14, http://dx.doi.org/10.1080/00031305.2023.2249522
    Journal articles | 2024
    Vu BA; Gunawan D; Zammit-Mangion A, 2024, 'Correction to: R-VGAL: a sequential variational Bayes algorithm for generalised linear mixed models (Statistics and Computing, (2024), 34, 3, (110), 10.1007/s11222-024-10422-8)', Statistics and Computing, 34, http://dx.doi.org/10.1007/s11222-024-10469-7
    Journal articles | 2024
    Vu BA; Gunawan D; Zammit-Mangion A, 2024, 'R-VGAL: a sequential variational Bayes algorithm for generalised linear mixed models', Statistics and Computing, 34, http://dx.doi.org/10.1007/s11222-024-10422-8
    Journal articles | 2024
    Zammit-Mangion A; Kaminski MD; Tran BH; Filippone M; Cressie N, 2024, 'Spatial Bayesian neural networks', Spatial Statistics, 60, http://dx.doi.org/10.1016/j.spasta.2024.100825
    Journal articles | 2023
    Burr WS; Newlands NK; Zammit-Mangion A, 2023, 'Environmental data science: Part 2', Environmetrics, 34, http://dx.doi.org/10.1002/env.2788
    Journal articles | 2023
    Byrne B; Baker DF; Basu S; Bertolacci M; Bowman KW; Carroll D; Chatterjee A; Chevallier F; Ciais P; Cressie N; Crisp D; Crowell S; Deng F; Deng Z; Deutscher NM; Dubey MK; Feng S; García OE; Griffith DWT; Herkommer B; Hu L; Jacobson AR; Janardanan R; Jeong S; Johnson MS; Jones DBA; Kivi R; Liu J; Liu Z; Maksyutov S; Miller JB; Miller SM; Morino I; Notholt J; Oda T; O'Dell CW; Oh YS; Ohyama H; Patra PK; Peiro H; Petri C; Philip S; Pollard DF; Poulter B; Remaud M; Schuh A; Sha MK; Shiomi K; Strong K; Sweeney C; Té Y; Tian H; Velazco VA; Vrekoussis M; Warneke T; Worden JR; Wunch D; Yao Y; Yun J; Zammit-Mangion A; Zeng N, 2023, 'National CO2 budgets (2015-2020) inferred from atmospheric CO2 observations in support of the global stocktake', Earth System Science Data, 15, pp. 963 - 1004, http://dx.doi.org/10.5194/essd-15-963-2023
    Journal articles | 2023
    Cartwright L; Zammit-Mangion A; Deutscher NM, 2023, 'Emulation of greenhouse-gas sensitivities using variational autoencoders', Environmetrics, 34, http://dx.doi.org/10.1002/env.2754
    Journal articles | 2023
    Cressie N; Zammit-Mangion A; Jacobson J; Bertolacci M, 2023, 'Earth’s CO2 battle: a view from space', Significance, 20, pp. 14 - 19, http://dx.doi.org/10.1093/jrssig/qmad003
    Journal articles | 2023
    Gaubert B; Stephens BB; Baker DF; Basu S; Bertolacci M; Bowman KW; Buchholz R; Chatterjee A; Chevallier F; Commane R; Cressie N; Deng F; Jacobs N; Johnson MS; Maksyutov SS; McKain K; Liu J; Liu Z; Morgan E; O’Dell C; Philip S; Ray E; Schimel D; Schuh A; Taylor TE; Weir B; van Wees D; Wofsy SC; Zammit-Mangion A; Zeng N, 2023, 'Neutral Tropical African CO2 Exchange Estimated From Aircraft and Satellite Observations', Global Biogeochemical Cycles, 37, http://dx.doi.org/10.1029/2023GB007804
    Journal articles | 2023
    Jacobson J; Cressie N; Zammit-Mangion A, 2023, 'Spatial Statistical Prediction of Solar-Induced Chlorophyll Fluorescence (SIF) from Multivariate OCO-2 Data', Remote Sensing, 15, http://dx.doi.org/10.3390/rs15164038
    Journal articles | 2023
    Ng TLJ; Zammit-Mangion A, 2023, 'Non-homogeneous Poisson process intensity modeling and estimation using measure transport', Bernoulli, 29, pp. 815 - 838, http://dx.doi.org/10.3150/22-BEJ1480
    Journal articles | 2023
    Vu Q; Zammit-Mangion A; Chuter SJ, 2023, 'Constructing large nonstationary spatio-temporal covariance models via compositional warpings', Spatial Statistics, 54, http://dx.doi.org/10.1016/j.spasta.2023.100742
    Journal articles | 2023
    Wikle CK; Mateu J; Zammit-Mangion A, 2023, 'Deep learning and spatial statistics', Spatial Statistics, 57, http://dx.doi.org/10.1016/j.spasta.2023.100774
    Journal articles | 2023
    Wikle CK; Zammit-Mangion A, 2023, 'Statistical Deep Learning for Spatial and Spatiotemporal Data', Annual Review of Statistics and Its Application, 10, pp. 247 - 270, http://dx.doi.org/10.1146/annurev-statistics-033021-112628
    Journal articles | 2023
    Zammit-Mangion A; Newlands NK; Burr WS, 2023, 'Environmental data science: Part 1', Environmetrics, 34, http://dx.doi.org/10.1002/env.2787
    Journal articles | 2022
    Beck B; Zammit-Mangion A; Fry R; Smith K; Gabbe B, 2022, 'Spatiotemporal mapping of major trauma in Victoria, Australia', Plos One, 17, http://dx.doi.org/10.1371/journal.pone.0266521
    Journal articles | 2022
    Chuter SJ; Zammit-Mangion A; Rougier J; Dawson G; Bamber JL, 2022, 'Mass evolution of the Antarctic Peninsula over the last 2 decades from a joint Bayesian inversion', Cryosphere, 16, pp. 1349 - 1367, http://dx.doi.org/10.5194/tc-16-1349-2022
    Journal articles | 2022
    Cressie N; Bertolacci M; Zammit-Mangion A, 2022, 'From Many to One: Consensus Inference in a MIP', Geophysical Research Letters, 49, http://dx.doi.org/10.1029/2022GL098277
    Journal articles | 2022
    Cressie N; Sainsbury-Dale M; Zammit-Mangion A, 2022, 'Basis-Function Models in Spatial Statistics', Annual Review of Statistics and Its Application, 9, pp. 373 - 400, http://dx.doi.org/10.1146/annurev-statistics-040120-020733
    Journal articles | 2022
    Ng TLJ; Zammit-Mangion A, 2022, 'Spherical Poisson point process intensity function modeling and estimation with measure transport', Spatial Statistics, 50, http://dx.doi.org/10.1016/j.spasta.2022.100629
    Journal articles | 2022
    Stell AC; Bertolacci M; Zammit-Mangion A; Rigby M; Fraser PJ; Harth CM; Krummel PB; Lan X; Manizza M; Mühle J; O'Doherty S; Prinn RG; Weiss RF; Young D; Ganesan AL, 2022, 'Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion', Atmospheric Chemistry and Physics, 22, pp. 12945 - 12960, http://dx.doi.org/10.5194/acp-22-12945-2022
    Journal articles | 2022
    Vu Q; Zammit-Mangion A; Cressie N, 2022, 'MODELING NONSTATIONARY AND ASYMMETRIC MULTIVARIATE SPATIAL COVARIANCES VIA DEFORMATIONS', Statistica Sinica, 32, pp. 2071 - 2093, http://dx.doi.org/10.5705/ss.202020.0156
    Journal articles | 2022
    Zammit-Mangion A; Bertolacci M; Fisher J; Stavert A; Rigby M; Cao Y; Cressie N, 2022, 'WOMBAT v1.0: A fully Bayesian global flux-inversion framework', Geoscientific Model Development, 15, pp. 45 - 73, http://dx.doi.org/10.5194/gmd-15-45-2022
    Journal articles | 2022
    Zammit-Mangion A; Ng TLJ; Vu Q; Filippone M, 2022, 'Deep Compositional Spatial Models', Journal of the American Statistical Association, 117, pp. 1787 - 1808, http://dx.doi.org/10.1080/01621459.2021.1887741
    Journal articles | 2021
    Huang HC; Cressie N; Zammit-Mangion A; Huang G, 2021, 'False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data', Journal of Computational and Graphical Statistics, 30, pp. 1081 - 1094, http://dx.doi.org/10.1080/10618600.2021.1873144
    Journal articles | 2021
    Vu Q; Cao Y; Jacobson J; Pearse AR; Zammit-Mangion A, 2021, 'Discussion on “Competition on Spatial Statistics for Large Datasets”', Journal of Agricultural Biological and Environmental Statistics, 26, pp. 614 - 618, http://dx.doi.org/10.1007/s13253-021-00464-0
    Journal articles | 2021
    Zammit-Mangion A; Cressie N, 2021, 'Frk: An r package for spatial and spatio-temporal prediction with large datasets', Journal of Statistical Software, 98, http://dx.doi.org/10.18637/jss.v098.i04
    Journal articles | 2020
    Yoo EH; Zammit-Mangion A; Chipeta MG, 2020, 'Adaptive spatial sampling design for environmental field prediction using low-cost sensing technologies', Atmospheric Environment, 221, http://dx.doi.org/10.1016/j.atmosenv.2019.117091
    Journal articles | 2020
    Zammit-Mangion A; Rougier J, 2020, 'Multi-scale process modelling and distributed computation for spatial data', Statistics and Computing, 30, pp. 1609 - 1627, http://dx.doi.org/10.1007/s11222-020-09962-6
    Journal articles | 2020
    Zammit-Mangion A; Wikle CK, 2020, 'Deep integro-difference equation models for spatio-temporal forecasting', Spatial Statistics, 37, http://dx.doi.org/10.1016/j.spasta.2020.100408
    Journal articles | 2020
    Zammit-Mangion A, 2020, 'Discussion on A high-resolution bilevel skew-t stochastic generator for assessing Saudi Arabia's wind energy resources', Environmetrics, 31, http://dx.doi.org/10.1002/env.2649
    Journal articles | 2019
    Cartwright L; Zammit-Mangion A; Bhatia S; Schroder I; Phillips F; Coates T; Negandhi K; Naylor T; Kennedy M; Zegelin S; Wokker N; Deutscher NM; Feitz A, 2019, 'Bayesian atmospheric tomography for detection and quantification of methane emissions: Application to data from the 2015 Ginninderra release experiment', Atmospheric Measurement Techniques, 12, pp. 4659 - 4676, http://dx.doi.org/10.5194/amt-12-4659-2019
    Journal articles | 2019
    Heaton MJ; Datta A; Finley AO; Furrer R; Guinness J; Guhaniyogi R; Gerber F; Gramacy RB; Hammerling D; Katzfuss M; Lindgren F; Nychka DW; Sun F; Zammit-Mangion A, 2019, 'A Case Study Competition Among Methods for Analyzing Large Spatial Data', Journal of Agricultural Biological and Environmental Statistics, 24, pp. 398 - 425, http://dx.doi.org/10.1007/s13253-018-00348-w
    Journal articles | 2019
    Suesse T; Zammit-Mangion A, 2019, 'Marginal maximum likelihood estimation of conditional autoregressive models with missing data', Stat, 8, http://dx.doi.org/10.1002/sta4.226
    Journal articles | 2018
    Zammit-Mangion A; Cressie N; Shumack C, 2018, 'On statistical approaches to generate Level 3 products from satellite remote sensing retrievals', Remote Sensing, 10, http://dx.doi.org/10.3390/rs10010155
    Journal articles | 2018
    Zammit-Mangion A; Rougier J, 2018, 'A sparse linear algebra algorithm for fast computation of prediction variances with Gaussian Markov random fields', Computational Statistics and Data Analysis, 123, pp. 116 - 130, http://dx.doi.org/10.1016/j.csda.2018.02.001
    Journal articles | 2017
    Martin-Español A; Bamber JL; Zammit-Mangion A, 2017, 'Constraining the mass balance of East Antarctica', Geophysical Research Letters, 44, pp. 4168 - 4175, http://dx.doi.org/10.1002/2017GL072937
    Journal articles | 2017
    Suesse T; Zammit-Mangion A, 2017, 'Computational aspects of the EM algorithm for spatial econometric models with missing data', Journal of Statistical Computation and Simulation, 87, pp. 1767 - 1786, http://dx.doi.org/10.1080/00949655.2017.1286495
    Journal articles | 2016
    Cressie N; Zammit-Mangion A, 2016, 'Multivariate spatial covariance models: A conditional approach', Biometrika, 103, pp. 915 - 935, http://dx.doi.org/10.1093/biomet/asw045
    Journal articles | 2016
    Cseke B; Zammit-Mangion A; Heskes T; Sanguinetti G, 2016, 'Sparse Approximate Inference for Spatio-Temporal Point Process Models', Journal of the American Statistical Association, 111, pp. 1746 - 1763, http://dx.doi.org/10.1080/01621459.2015.1115357
    Journal articles | 2016
    Martín-Español A; King MA; Zammit-Mangion A; Andrews SB; Moore P; Bamber JL, 2016, 'An assessment of forward and inverse GIA solutions for Antarctica', Journal of Geophysical Research Solid Earth, 121, pp. 6947 - 6965, http://dx.doi.org/10.1002/2016JB013154
    Journal articles | 2016
    Martín-Español A; Zammit-Mangion A; Clarke PJ; Flament T; Helm V; King MA; Luthcke SB; Petrie E; Rémy F; Schön N; Wouters B; Bamber JL, 2016, 'Spatial and temporal Antarctic Ice Sheet mass trends, glacio-isostatic adjustment, and surface processes from a joint inversion of satellite altimeter, gravity, and GPS data', Journal of Geophysical Research Earth Surface, 121, pp. 182 - 200, http://dx.doi.org/10.1002/2015JF003550
    Journal articles | 2016
    Rougier J; Zammit-Mangion A, 2016, 'Visualization for Large-scale Gaussian Updates', Scandinavian Journal of Statistics, 43, pp. 1153 - 1161, http://dx.doi.org/10.1111/sjos.12234
    Journal articles | 2016
    Zammit-Mangion A; Cressie N; Ganesan AL, 2016, 'Non-Gaussian bivariate modelling with application to atmospheric trace-gas inversion', Spatial Statistics, 18, pp. 194 - 220, http://dx.doi.org/10.1016/j.spasta.2016.06.005
    Journal articles | 2015
    Cressie N; Burden S; Davis W; Krivitsky PN; Mokhtarian P; Suesse T; Zammit-Mangion A, 2015, 'Capturing multivariate spatial dependence: Model, estimate and then predict', Statistical Science, 30, pp. 170 - 175, http://dx.doi.org/10.1214/15-STS517
    Journal articles | 2015
    Schoen N; Zammit-Mangion A; Rougier JC; Flament T; Rémy F; Luthcke S; Bamber JL, 2015, 'Simultaneous solution for mass trends on the West Antarctic Ice Sheet', Cryosphere, 9, pp. 805 - 819, http://dx.doi.org/10.5194/tc-9-805-2015
    Journal articles | 2015
    Zammit-Mangion A; Bamber JL; Schoen NW; Rougier JC, 2015, 'A data-driven approach for assessing ice-sheet mass balance in space and time', Annals of Glaciology, 56, pp. 175 - 183, http://dx.doi.org/10.3189/2015AoG70A021
    Journal articles | 2015
    Zammit-Mangion A; Cressie N; Ganesan AL; O'Doherty S; Manning AJ, 2015, 'Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion', Chemometrics and Intelligent Laboratory Systems, 149, pp. 227 - 241, http://dx.doi.org/10.1016/j.chemolab.2015.09.006
    Journal articles | 2015
    Zammit-Mangion A; Rougier J; Schön N; Lindgren F; Bamber J, 2015, 'Multivariate spatio-temporal modelling for assessing Antarctica's present-day contribution to sea-level rise', Environmetrics, 26, pp. 159 - 177, http://dx.doi.org/10.1002/env.2323
    Journal articles | 2014
    Ganesan AL; Rigby M; Zammit-Mangion A; Manning AJ; Prinn RG; Fraser PJ; Harth CM; Kim KR; Krummel PB; Li S; Mühle J; O'Doherty SJ; Park S; Salameh PK; Steele LP; Weiss RF, 2014, 'Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods', Atmospheric Chemistry and Physics, 14, pp. 3855 - 3864, http://dx.doi.org/10.5194/acp-14-3855-2014
    Journal articles | 2014
    Zammit-Mangion A; Rougier J; Bamber J; Schön N, 2014, 'Resolving the Antarctic contribution to sea-level rise: A hierarchical modelling framework', Environmetrics, 25, pp. 245 - 264, http://dx.doi.org/10.1002/env.2247
    Journal articles | 2013
    Menzies RI; Zammit-Mangion A; Hollis LM; Lennen RJ; Jansen MA; Webb DJ; Mullins JJ; Dear JW; Sanguinetti G; Bailey MA, 2013, 'An anatomically unbiased approach for analysis of renal BOLD magnetic resonance images', American Journal of Physiology Renal Physiology, 305, pp. F845 - F852, http://dx.doi.org/10.1152/ajprenal.00113.2013
    Journal articles | 2013
    Zammit-Mangion A; Dewar M; Kadirkamanathan V; Flesken A; Sanguinetti G, 2013, 'Conflict data sets and point patterns', Springerbriefs in Applied Sciences and Technology, pp. 1 - 14, http://dx.doi.org/10.1007/978-3-319-01038-0_1
    Journal articles | 2013
    Zammit-Mangion A; Dewar M; Kadirkamanathan V; Flesken A; Sanguinetti G, 2013, 'Modeling and prediction in conflict: Afghanistan', Springerbriefs in Applied Sciences and Technology, pp. 47 - 66, http://dx.doi.org/10.1007/978-3-319-01038-0_3
    Journal articles | 2013
    Zammit-Mangion A; Dewar M; Kadirkamanathan V; Flesken A; Sanguinetti G, 2013, 'Theory', Springerbriefs in Applied Sciences and Technology, pp. 15 - 46, http://dx.doi.org/10.1007/978-3-319-01038-0_2
    Journal articles | 2013
    Zammit-Mangion A, 2013, 'Foreword', Springerbriefs in Applied Sciences and Technology, pp. i - iv
    Journal articles | 2012
    Zammit-Mangion A; Dewar M; Kadirkamanathan V; Sanguinetti G, 2012, 'Point process modelling of the Afghan War Diary', Proceedings of the National Academy of Sciences of the United States of America, 109, pp. 12414 - 12419, http://dx.doi.org/10.1073/pnas.1203177109
    Journal articles | 2012
    Zammit-Mangion A; Sanguinetti G; Kadirkamanathan V, 2012, 'Variational estimation in spatiotemporal systems from continuous and point-process observations', IEEE Transactions on Signal Processing, 60, pp. 3449 - 3459, http://dx.doi.org/10.1109/TSP.2012.2191966
    Journal articles | 2011
    Zammit Mangion A; Anderson SR; Kadirkamanathan V, 2011, 'Exploration and control of stochastic spatiotemporal systems with mobile agents', IFAC Proceedings Volumes IFAC Papersonline, 44, pp. 4489 - 4494, http://dx.doi.org/10.3182/20110828-6-IT-1002.01503
    Journal articles | 2011
    Zammit Mangion A; Sanguinetti G; Kadirkamanathan V, 2011, 'A variational approach for the online dual estimation of spatiotemporal systems governed by the IDE', IFAC Proceedings Volumes IFAC Papersonline, 44, pp. 3204 - 3209, http://dx.doi.org/10.3182/20110828-6-IT-1002.02459
    Journal articles | 2011
    Zammit Mangion A; Yuan K; Kadirkamanathan V; Niranjan M; Sanguinetti G, 2011, 'Online variational inference for state-space models with point-process observations', Neural Computation, 23, pp. 1967 - 1999, http://dx.doi.org/10.1162/NECO_a_00156
  • Preprints | 2026
    Nag P; Zammit-Mangion A; Singh S; Cressie N, 2026, Spatio-temporal modeling and forecasting with Fourier neural operators, http://dx.doi.org/10.48550/arxiv.2601.01813
    Preprints | 2026
    Ng TLJ; Kwong K-K; Liu J; Zammit-Mangion A, 2026, Bayesian Sphere-on-Sphere Regression with Optimal Transport Maps, http://dx.doi.org/10.48550/arxiv.2501.08492
    Preprints | 2026
    Patterson C; Zammit-Mangion A; Xue Z; Zhang K; Zhou Z; Timms W; Feitz A, 2026, The Otway Shallow Fault Experiment: Insights from surface monitoring, http://dx.doi.org/10.2139/ssrn.6041639
    Preprints | 2026
    Sainsbury-Dale M; Zammit-Mangion A; Cressie N; Huser R, 2026, Neural Parameter Estimation with Incomplete Data, http://dx.doi.org/10.48550/arxiv.2501.04330
    Preprints | 2026
    Walchessen J; Zammit-Mangion A; Huser R; Kuusela M, 2026, Neural Conditional Simulation for Complex Spatial Processes, http://dx.doi.org/10.48550/arxiv.2508.20067
    Preprints | 2025
    Bertolacci M; Zammit-Mangion A; Giraldo JV; O'Neill M; Bransby F; Watson P, 2025, GeoWarp: Warped spatial processes for inferring subsea sediment properties, http://dx.doi.org/10.48550/arxiv.2501.07841
    Preprints | 2025
    Jacobson J; Bertolacci M; Zammit-Mangion A; Schuh A; Cressie N, 2025, WOMBAT v2.S: A Bayesian inversion framework for attributing global CO$_2$ flux components from multiprocess data, http://dx.doi.org/10.48550/arxiv.2503.09065
    Preprints | 2025
    Sainsbury-Dale M; Zammit-Mangion A; Richards J; Huser R, 2025, Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks, http://dx.doi.org/10.48550/arxiv.2310.02600
    Preprints | 2025
    Vu Q; Shao X; Huser R; Zammit-Mangion A, 2025, deepspat: An R package for modeling nonstationary spatial and spatio-temporal Gaussian and extremes data through deep deformations, http://dx.doi.org/10.48550/arxiv.2512.08137
    Other | 2025
    de Kreij R; Zammit Mangion A; Rayson M; Jones N; Zulberti A, 2025, Statistical inversion of surface tracers to infer fine-scale near-surface ocean currents, http://dx.doi.org/10.5194/egusphere-egu25-10550
    Preprints | 2024
    Zammit-Mangion A; Kaminski MD; Tran B-H; Filippone M; Cressie N, 2024, Spatial Bayesian Neural Networks, http://dx.doi.org/10.48550/arxiv.2311.09491
    Preprints | 2024
    Zammit-Mangion A; Sainsbury-Dale M; Huser R, 2024, Neural Methods for Amortized Inference, http://dx.doi.org/10.48550/arxiv.2404.12484
    Other | 2023
    Chuter S; Zammit-Mangion A; Bamber J; Benveniste J, 2023, Monthly sea level fingerprints from 1992-2017, utilising ESA CCI Essential Climate Variables in an ensemble modelling framework, http://dx.doi.org/10.5194/egusphere-egu23-8047
    Preprints | 2023
    Ng TLJ; Zammit-Mangion A, 2023, Mixture Modeling with Normalizing Flows for Spherical Density Estimation, http://dx.doi.org/10.48550/arxiv.2301.06404
    Preprints | 2023
    Sainsbury-Dale M; Zammit-Mangion A; Huser R, 2023, Likelihood-Free Parameter Estimation with Neural Bayes Estimators, http://dx.doi.org/10.48550/arxiv.2208.12942
    Preprints | 2023
    Vu Q; Moores MT; Zammit-Mangion A, 2023, Warped Gradient-Enhanced Gaussian Process Surrogate Models for Exponential Family Likelihoods with Intractable Normalizing Constants, http://dx.doi.org/10.48550/arxiv.2105.04374
    Preprints | 2023
    Vu Q; Zammit-Mangion A; Chuter SJ, 2023, Constructing Large Nonstationary Spatio-Temporal Covariance Models via Compositional Warpings, http://dx.doi.org/10.48550/arxiv.2202.03560
    Preprints | 2023
    Yoo E-H; Zammit-Mangion A; Chipeta MG, 2023, Adaptive Spatial Sampling Design for Environmental Field Prediction using Low-Cost Sensing Technologies, http://dx.doi.org/10.48550/arxiv.2303.02050
    Preprints | 2022
    Bertolacci M; Zammit-Mangion A; Schuh A; Bukosa B; Fisher J; Cao Y; Kaushik A; Cressie N, 2022, Inferring changes to the global carbon cycle with WOMBAT v2.0, a hierarchical flux-inversion framework, http://dx.doi.org/10.48550/arxiv.2210.10479
    Preprints | 2022
    Cressie N; Sainsbury-Dale M; Zammit-Mangion A, 2022, Basis-Function Models in Spatial Statistics, http://dx.doi.org/10.48550/arxiv.2202.03660
    Preprints | 2022
    Ng TLJ; Zammit-Mangion A, 2022, Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport, http://dx.doi.org/10.48550/arxiv.2007.00248
    Preprints | 2022
    Ng TLJ; Zammit-Mangion A, 2022, Spherical Poisson Point Process Intensity Function Modeling and Estimation with Measure Transport, http://dx.doi.org/10.48550/arxiv.2201.09485
    Preprints | 2022
    Sainsbury-Dale M; Zammit-Mangion A; Cressie N, 2022, Modelling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data using FRK, http://dx.doi.org/10.48550/arxiv.2110.02507
    Other | 2022
    Stell AC; Bertolacci M; Zammit-Mangion A; Rigby M; Fraser PJ; Harth CM; Krummel PB; Lan X; Manizza M; Mühle J; O'Doherty S; Prinn RG; Weiss RF; Young D; Ganesan AL, 2022, Supplementary material to "Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion", http://dx.doi.org/10.5194/egusphere-2022-513-supplement
    Preprints | 2022
    Wikle CK; Zammit-Mangion A, 2022, Statistical Deep Learning for Spatial and Spatio-Temporal Data, http://dx.doi.org/10.48550/arxiv.2206.02218
    Other | 2021
    Chuter SJ; Zammit-Mangion A; Rougier J; Dawson G; Bamber JL, 2021, Supplementary material to "Mass evolution of the Antarctic Peninsula over the last two decades from a joint Bayesian inversion", http://dx.doi.org/10.5194/tc-2021-178-supplement
    Preprints | 2020
    Huang H-C; Cressie N; Zammit-Mangion A; Huang G, 2020, False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data, http://dx.doi.org/10.48550/arxiv.1905.06268
    Preprints | 2020
    Zammit-Mangion A; Ng TLJ; Vu Q; Filippone M, 2020, Deep Compositional Spatial Models, http://dx.doi.org/10.48550/arxiv.1906.02840
    Preprints | 2020
    Zammit-Mangion A; Rougier J, 2020, Multi-Scale Process Modelling and Distributed Computation for Spatial Data, http://dx.doi.org/10.48550/arxiv.1907.07813
    Preprints | 2020
    Zammit-Mangion A; Wikle CK, 2020, Deep Integro-Difference Equation Models for Spatio-Temporal Forecasting, http://dx.doi.org/10.48550/arxiv.1910.13524
    Preprints | 2019
    Cartwright L; Zammit-Mangion A; Bhatia S; Schroder I; Phillips F; Coates T; Neghandhi K; Naylor T; Kennedy M; Zegelin S; Wokker N; Deutscher NM; Feitz A, 2019, Bayesian atmospheric tomography for detection and quantification of methane emissions: Application to data from the 2015 Ginninderra release experiment, http://dx.doi.org/10.5194/amt-2019-124
    Preprints | 2018
    Heaton MJ; Datta A; Finley A; Furrer R; Guhaniyogi R; Gerber F; Gramacy RB; Hammerling D; Katzfuss M; Lindgren F; Nychka DW; Sun F; Zammit-Mangion A, 2018, A Case Study Competition Among Methods for Analyzing Large Spatial Data, http://dx.doi.org/10.48550/arxiv.1710.05013
    Preprints | 2018
    Zammit-Mangion A; Cressie N; Shumack C, 2018, On statistical approaches to generate Level 3 products from satellite remote sensing retrievals, http://dx.doi.org/10.48550/arxiv.1711.07629
    Preprints | 2018
    Zammit-Mangion A; Cressie N, 2018, FRK: An R Package for Spatial and Spatio-Temporal Prediction with Large Datasets, http://dx.doi.org/10.48550/arxiv.1705.08105
    Preprints | 2018
    Zammit-Mangion A; Rougier J, 2018, A sparse linear algebra algorithm for fast computation of prediction variances with Gaussian Markov random fields, http://dx.doi.org/10.48550/arxiv.1707.00892
    Preprints | 2016
    Cressie N; Zammit-Mangion A, 2016, Multivariate Spatial Covariance Models: A Conditional Approach, http://dx.doi.org/10.48550/arxiv.1504.01865
    Preprints | 2016
    Zammit-Mangion A; Cressie N; Ganesan AL, 2016, Non-Gaussian bivariate modelling with application to atmospheric trace-gas inversion, http://dx.doi.org/10.48550/arxiv.1606.04564
    Preprints | 2015
    Zammit-Mangion A; Cressie N; Ganesan AL; Doherty SO; Manning AJ, 2015, Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion, http://dx.doi.org/10.48550/arxiv.1509.00915
    Conference Papers | 2010
    Mills AR; Apopei B; Mangion AZ; Barron-Gonzales H; Gunetti P; Thompson HA; Garbett P, 2010, 'Heterogeneous hardware technologies for accelerating complex aerospace system simulations', in IEEE Aerospace Conference Proceedings, http://dx.doi.org/10.1109/AERO.2010.5446789
    Conference Papers | 2008
    Knake-Langhorst S; Zammit-Mangion A, 2008, 'Usability of local traffic density as basis for advanced driver assistance systems', in Fisita World Automotive Congress 2008 Congress Proceedings Vehicle Safety, pp. 344 - 353
    Preprints |
    Beck B; Zammit-Mangion A; Fry R; Smith K; Gabbe B, Spatiotemporal mapping of major trauma in Victoria, Australia, http://dx.doi.org/10.1101/2021.11.21.21266663
    Preprints |
    Chuter SJ; Zammit-Mangion A; Rougier J; Dawson G; Bamber JL, Mass evolution of the Antarctic Peninsula over the last two decades from a joint Bayesian inversion, http://dx.doi.org/10.5194/tc-2021-178
    Preprints |
    Stell AC; Bertolacci M; Zammit-Mangion A; Rigby M; Fraser PJ; Harth CM; Krummel PB; Lan X; Manizza M; Mühle J; O'Doherty S; Prinn RG; Weiss RF; Young D; Ganesan AL, Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion, http://dx.doi.org/10.5194/egusphere-2022-513
    Preprints |
    Zammit-Mangion A; Bertolacci M; Fisher J; Stavert A; Rigby ML; Cao Y; Cressie N, WOMBAT v1.0: A fully Bayesian global flux-inversion framework, http://dx.doi.org/10.5194/gmd-2021-181

12.2023 National Aeronautics and Space Administration (NASA) Research Opportunities in Space and Earth Science (ROSES). “Constraining carbon fluxes and transport patterns using new spatiotemporal information in remotely sensed CO2,” 2024-2027. Co-Investigator.

12.2023 National Aeronautics and Space Administration (NASA) Research Opportunities in Space and Earth Science (ROSES). “Hierarchical Spatio-Temporal Statistical Methods for Analyzing OCO-2/3 Data,” 2021-2024. Co-Investigator. 

09.2023 King Abdullah University of Science and Technology (KAUST) Opportunity Fund Program (OFP). “Neural Estimators for Fast Optimal Inference with Intractable Statistical Models in Complex Settings,” 2024-2025. Co-Investigator (Lead at Host Institution).

09.2023 US Air Force Office of Scientific Research (AFOSR) Research Interests of the Air Force Office of Scientific Research Department of Defense. “Bayesian Spatio-Temporal Analysis and Statistical Computation in Very High Dimensional Problems”. Co-Investigator. 

03.2021 National Aeronautics and Space Administration (NASA) Research Opportunities in Space and Earth Science (ROSES). “Spatio-Temporal Statistical Methods for Producing OCO-2/OCO-3 Level 3 and Level 4 Estimates,” 2021-2024. Co-Investigator. 

07.2020 Australian Research Council: Industrial Transformation Research Hub (ITRH). “ARC Research Hub for Transforming Energy Infrastructure Through Digital Engineering,” 2021-2026. Chief Investigator (Lead at Host Institution). Total 

05.2020 Australian Research Council: Special Research Initiative (SRI). “Securing Antarctica’s Environmental Future,” 2021-2027. Chief Investigator.

11.2018 Australian Research Council: Discovery Project (DP). “Bayesian inversion and computation applied to atmospheric flux fields,” 2019-2022. Chief Investigator.

04.2018 National Aeronautics and Space Administration (NASA) Research Opportunities in Space and Earth Science (ROSES). “Spatial Statistical Analysis of OCO-2 Data,” 2018-2021. Co-Principal Investigator. 

11.2017 Australian Research Council: Discovery Early Career Researcher Award (DECRA). “Deep space-time models for modelling complex environmental phenomena,” 2018-2022. Lead Chief Investigator. 

 

08.2024 University of Wollongong Vice-Chancellor Team Research Excellence Award, acknowledging outstanding contributions to research by a team of UOW researchers who are collaborating across discipline boundaries and who have combined their expertise to produce achievements of outstanding international significance. 

12.2023 The Statistical Society of Australia Horizon Lecture Award, recognising emerging leaders in Australia's statistics community, and their contributions to advancing statistical practice.  

08.2023 The American Statistical Association Statistics in Physical and Engineering Sciences (SPES) Award in the innovative use of statistics to solve a high-impact problem in the physical and engineering sciences. 

08.2023 The American Statistical Association Outstanding Statistical Application Award in recognition of a paper demonstrating an outstanding application of statistics in any substantive field.

08.2023 The International Society for Bayesian Analysis Mitchell Prize in recognition of an outstanding paper that describes how a Bayesian analysis has solved an important applied problem.

07.2023 The Statistical Society of Australia Venables Award for an open-source software contribution that makes a clear impact for the practice of data science or statistics.

04.2022 The American Statistical Association Section on Statistics and the Environment ENVR Early Investigator Award, in recognition of highly impactful methodological and interdisciplinary research in spatio-temporal statistics applied to investigating causes and effects of a changing climate, for the development of important computational-statistical tools and related software, and for service to the profession.

12.2020 Awarded status of Elected Member of the International Statistical Institute (ISI).

05.2020 Taylor & Francis Outstanding Reference/Monograph in the Science and Medical category published in 2019 (for the book Spatio-Temporal Statistics with R).

04.2020 The International Environmetrics Society Abdel El-Shaarawi Early Investigator Award, in recognition of interdisciplinary work in Environmental Statistics and in the development of important computational instruments for space-time data analysis.

04.2013 National Academy of Sciences of the USA Cozzarelli Prize for PNAS paper of outstanding excellence and originality in Engineering and Applied Sciences, Washington DC, USA.

11.2012 Institute of Engineering and Technology (IET) Control and Automation Best Doctoral Dissertation Prize, London, UK.

10.2008 Best Student Paper at the UK Automatic Control Council (UKACC) Conference, Manchester, UK.

07.2007 Prize for Best Academic Achievement (sponsored by electronics company RS) at the Faculty of Engineering, University of Malta.

My research interests lie broadly in spatio-temporal modelling and the statistical and computational tools that enable inference for complex, large-scale systems. I am particularly interested in models that accommodate nonstationarity, non-Gaussianity, multivariate dependence, and massive data volumes, while providing principled uncertainty quantification.

A major focus of my research involves environmental applications. This includes work on assessing Antarctica’s contribution to sea-level rise through the fusion of heterogeneous satellite and observational data, and on estimating the spatio-temporal distribution of greenhouse gas sources and sinks. These projects typically involve large-scale spatio-temporal models, high-performance and GPU computing, sparse linear algebra, and parallel inference algorithms.

More recently, my research has focused on integrating deep learning methods with spatio-temporal statistical modelling. The aim of this work is to leverage the representational power of modern machine learning while retaining the interpretability, structure, and uncertainty quantification offered by statistical models, particularly for environmental and geophysical applications.

My Research Supervision

Vinicius Ricardo Riffel (PhD, University of Wollongong, Primary Supervisor)

Daniel Fynn (PhD, University of Wollongong, Co-Supervisor)

Rick de Kreij (PhD, University of Western Australia, Associate Supervisor)