Research Projects

I have had the privilege to work on several projects of a diverse nature during my undergraduate,  Ph.D, and post-doctoral years. Below I list them according to topic (by date), with relevant publications, software and awards listed in each section. Further details can be found in the cited papers and I hope to add some brief description to each section in the future!

Univariate spatio-temporal modelling and inference

Thesis:

  • Zammit Mangion, A. (2011). Modelling from spatiotemporal data: a dynamic systems approach. Ph.D Thesis, University of Sheffield.

Articles:

  • Heaton, M.J., Datta, A., Finley, A., Furrer, R., Guinness, J., Guhaniyogi, R., Gerber, F.,  Gramacy, R.B., Hammerling, D., Katzfuss, M., Lindgren, F., Nychka, D.W., Sun F & Zammit-Mangion, A. (2019) A Case Study Competition among Methods for Analyzing Large Spatial Data, in press with the Journal of Agricultural, Biological, and Environmental Statistics.
  • Zammit-Mangion, A. & Rougier, J.C. (2018) A sparse linear algebra algorithm for fast computation of prediction variances with Gaussian Markov random fields. Computational Statistics & Data Analysis, 123, pp. 116-130.
  • Zammit-Mangion, A., Cressie, N. & Shumack, C. (2018) On statistical approaches to generate Level 3 products from statistical remote sensing retrievals. Remote Sensing, 10(1), 155.
  • Suesse, T., & Zammit-Mangion, A. (2017) Computational aspects of the EM algorithm for spatial econometric models with missing data,” Journal of Statistical Computing and Simulation, 87(9), pp. 1767–1786.
  • Cseke, B., Zammit-Mangion, A., Sanguinetti, G., & Heskes, T. (2016) Sparse approximations in spatio-temporal point-process models. Journal of the American Statistical Association, 111(516), pp. 1746-1763.
  • 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, 109(31), 12414-12419.
  • Zammit-Mangion, A., Sanguinetti, G., & Kadirkamanathan, V. (2012). Variational estimation in spatiotemporal systems from continuous and point-process observations. Signal Processing, IEEE Transactions on, 60(7), 3449-3459.
  • 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(8), 1967-1999.

Books:

  • Wikle, C.K., Zammit-Mangion, A., & N. Cressie (2019) Spatio-Temporal Statistics with R. Chapman & Hall/CRC: Boca Raton, FL.
  • Zammit-Mangion, A., Dewar, M., Kadirkamanathan, V., Flesken, A., & Sanguinetti, G. (2013). Modeling Conflict Dynamics with Spatio-temporal Data. Springer: New York, NY.

Short articles:

  • Wikle, C.K., Cressie, N., Zammit-Mangion, A., & Shumack, C. (2017). A Common Task Framework (CTF) for Objective Comparison of Spatial Prediction Methodologies. Statistics Views, online.

Conference proceedings:

  • Zammit Mangion, A., Sanguinetti, G., & Kadirkamanathan, V. (2011). A variational approach for the online dual estimation of spatiotemporal systems governed by the IDE. In Proceedings of the IFAC World Congress.

Awards:

  • Cozzarelli Prize: The National Academy of Sciences of the USA (April 2013) Prize for paper of “outsdanding scientific excellence and originality” in PNAS (http://www.pnas.org/site/misc/cozzarelliprize.xhtml). Winner in Class III (Engineering and Applied Sciences)
  • IET Ambition Award (November 2012) Best Doctoral Dissertation Prize in Control and Automation 2012

Large grants:

  • Australian Research Council: Discovery Early Career Researcher Award (DECRA). “Deep space-time models for modelling complex environmental phenomena.” Chief Investigator. Awarded AUD$348,575.

Small grants:

  • IMA (Institute of Mathematics and its Applications) Travel Grant (August 2013) Small grant scheme award to attend and present work at the 3rd Workshop on Latent Gaussian Models, Reykjavik, Iceland, 2013.
  • IAS (Institute of Advanced Studies) Workshop Grant (February 2013) Funds to organise a workshop on Spatiotemporal modelling with external speakers at the University of Bristol.
  • Research visit grant (November 2011) PASCAL Travel Grant for a 5-week research visit to the University of Edinburgh, UK.

Project pages:

Software:

  • R package FRK

 

Multi-variate spatial/spatio-temporal analysis and visualisation

Articles:

  • Cressie, N. and Zammit-Mangion, A. (2016). Multivariate spatial models: a conditional approach. Biometrika, 103(4), pp. 915–935.
  • Zammit-Mangion, A., Cressie, N., & Ganesan, A.L. (2016), Non-Gaussian bivariate modelling with application to atmospheric trace-gas inversion. Spatial Statistics, 18(A), pp. 194–220.
  • Rougier, J.C. and Zammit-Mangion, A. (2016), Computation and visualisation for large-scale Gaussian updates. Scandinavian Journal of Statistics, 43(4), pp. 1153–1161.
  • Zammit-Mangion, A., Cressie, N., Ganesan, A.L., O’Doherty, S., Manning, A.J. (2015). Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion. Chemometrics and Intelligent Laboratory Systems, 149(15), 227-241.
  • Zammit‐Mangion, A., Bamber, J., Schoen, N., & Rougier, J. (2015). A data-driven approach for assessing ice-sheet mass balance in space and time. Annals of Glaciology, 56, 175-183.
  • Zammit‐Mangion, A., Rougier, J., Bamber, J., & Schön, N. (2014). Resolving the Antarctic contribution to sea‐level rise: a hierarchical modelling framework. Environmetrics, 25(4), 245-264.
  • Zammit‐Mangion, A., Rougier, J., Schön, N., Lindgren, F. & Bamber, J. (in press). Multivariate spatio-temporal modelling for assessing Antarctica’s present-day contribution to sea-level rise. Environmetrics, 26(3), 159-177.
  • Schoen, N., Zammit-Mangion, A., Bamber, J. L., Rougier, J., Flament, T., Rémy, F., & Luthcke, S. B. (2014). Simultaneous solution for mass trends on the West Antarctic Ice Sheet. The Cryosphere, 9, 805-819.

Discussions:

  • Cressie, N., Burden, S., Davis, W., Krivitsky, P., Mokhtarian, P., Suesse, T., & Zammit-Mangion, A. Capturing Multivariate Spatial Dependence: Model, Estimate, and then Predict (2015). Discussion on “Cross-Covariance Functions for Multivariate Geostatistics” by Genton, M.G., & Kleiber, W., Statistical Science, 30, 170-175.

Large grants:

  • Australian Research Council: Discovery Project (DP). “Bayesian inversion and computation applied to atmospheric flux fields.” Co-Investigator with Noel Cressie. Awarded AUD$505,000.

Software:

Project pages:

Environmental sciences (application-focussed)

Articles:

  • Martin-Español, A., Bamber, J.L., & Zammit-Mangion, A. (2017). Constraining the mass balance of East Antarctica, Geophysical Research Letters, 44, doi:10.1002/2017GL072937.
  • Martín-Español, A., King, M.A., Zammit-Mangion, A., Andrews,S.B., Moore, P., & Bamber, J.L. (2016). An assessment of forward and inverse GIA solutions for Antarctica.  Journal of Geophysical Research: Solid Earth, 121(9), pp. 6947–6965.
  • Martín-Español, A., King, M.A., Zammit-Mangion, A., … & Bamber, J.L.  (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 (2016) Journal of Geophysical Research: Earth Surface, 121(2), pp. 182-200.
  • Ganesan, A. L., Rigby, M., Zammit-Mangion, A., Manning, A. J., Prinn, R. G., Fraser, P. J., … & Weiss, R. F. (2014). Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods. Atmospheric Chemistry and Physics, 14(8), 3855-3864.

Encyclopaedia entry:

  • Cressie, N., Burden, S., Shumack, C., Zammit-Mangion A., & Zhang, B. Environmental Informatics. Wiley StatsRef: Statistics Reference Online.

Small grants:

  • University of Wollongong Global Challenges Travel Award to the University of Bristol for work on carbon dioxide flux inversion from the OCO-2 satellite and global sea-level rise assessment. See here for details.

Image Analysis and Exceedances

Articles:

  • Menzies, R. I., Zammit-Mangion, A., Hollis, L. M., Lennen, R. J., Jansen, M. A., Webb, D. J., … & Bailey, M. A. (2013). An anatomically unbiased approach for analysis of renal BOLD magnetic resonance images. American Journal of Physiology-Renal Physiology, 305(6), F845-F852.

Software:

Robotics and Control

Conference proceedings:

  • Zammit Mangion, A., & Fabri, S. G. (2008). Experimental Evaluation of Haptic Control for Human Activated Command Devices. In Proc. UKACC International Conference of Control.
  • Zammit Mangion, A., Anderson, S. R., & Kadirkamanathan, V. (2011). Exploration and control of stochastic spatiotemporal systems with mobile agents. Proc. 18th IFAC World Congr, 4489-4494.
  • Mills, A. R., Apopei, B., Zammit Mangion, A., Barron-Gonzales, H., Gunetti, P., Thompson, H. A., & Garbett, P. (2010, March). Heterogeneous hardware technologies for accelerating complex aerospace system simulations. In Aerospace Conference, 2010, IEEE, 1-10.

Awards:

  • Best student paper (October 2008) Best student paper award at the UKACC Control Conference, Manchester, UK