Bertolacci, Michael

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.

Year	Title
2021	WOMBAT: A fully Bayesian global flux-inversion framework
2019	Climate inference on daily rainfall across the Australian continent, 1876¿2015 Published In Annals of Applied Statistics

Year	Title
2007	Are approximation algorithms for consensus clustering worthwhile? Published In Proceedings of the 7th SIAM International Conference on Data Mining
2006	New algorithms research for first year students Published In Working Group Reports on ITiCSE on Innovation and Technology in Computer Science Education 2006
2006	New algorithms research for first year students Published In ITiCSE06 - Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education

Year	Title
2021 - 2022	Spatio-Temporal Statistical Methods for Producing OCO-2/OCO-3 Level 3 and Level 4 Estimates Awarded by: NASA Funding Scheme: Research Opportunities in Space and Earth Sciences (ROSES)

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.

Year	Title
2021	WOMBAT: A fully Bayesian global flux-inversion framework
2019	Climate inference on daily rainfall across the Australian continent, 1876¿2015 Published In Annals of Applied Statistics

Year	Title
2007	Are approximation algorithms for consensus clustering worthwhile? Published In Proceedings of the 7th SIAM International Conference on Data Mining
2006	New algorithms research for first year students Published In Working Group Reports on ITiCSE on Innovation and Technology in Computer Science Education 2006
2006	New algorithms research for first year students Published In ITiCSE06 - Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education

Year	Title
2021 - 2022	Spatio-Temporal Statistical Methods for Producing OCO-2/OCO-3 Level 3 and Level 4 Estimates Awarded by: NASA Funding Scheme: Research Opportunities in Space and Earth Sciences (ROSES)

Bertolacci, Michael Dr