Michael Bertolacci

Research Fellow
Centre for Environmental Informatics, NIASRA
School of Mathematics and Applied Statistics
University of Wollongong, Australia

Telephone 02 4239 2388
Email michael_bertolacci {at}
UOW Scholars

Research Interests

I am interested in large scale spatio-temporal problems in environmental statistics. My previous research involved developing hierarchical Bayesian mixture models for the analysis of Australian daily rainfall at the continental scale. I also investigated methods for modelling multiple nonstationary time series in the spectral domain, as applied to spatial datasets including monthly rainfall and measles epidemiology.

My current research focuses on spatio-temporal flux inversion for trace gases using remotely sensed data.



Bertolacci, M., Cripps, E., Rosen, O., Lau, J. W., S. Cripps. (2019). Climate inference on daily rainfall across the Australian continent, 1876–2015. Annals of Applied Statistics, 13(2), pp 683–712. doi: 10.1214/18-AOAS1218.


Bertolacci, M., Cripps, E., Cripps, S., Lau, J. W. (2016). Bayesian mixture models for multivariate time series with an application to Australian rainfall data. Neural Information Processing Systems Time Series Workshop. Presented a poster at this workshop.


Wirth, A., Bertolacci, M. (2007). Are approximation algorithms for consensus clustering worthwhile? SIAM International Conference on Data Mining.


Wirth, A., Bertolacci, M. (2006). New algorithms research for first year students, 11th Annual ACM Conference on Innovation and Technology in Computer Science Education (ITICSE ’06), pp 128–32.



Last reviewed: 18 May, 2020