SSD SECS-S/02 – Statistics for experimental and technological research
Research interest My scientific interests concern the application of statistics in the fields of environmental sciences, technology, computer science, epidemiology and demography. I have been always interested in spatial statistics and one important topic of my research has been the theory of Markov random fields and Gibbs distributions, with applications in the fields of image analysis (classification of satellite data, NMR image analysis), epidemiology (disease mapping, ecological analysis) and demography (geographical mapping of mortality risk, mortality surfaces analysis, business demography). Other relevant topics concern the analysis of counts data, mixture models, non parametric regressions (cubic and B-splines, K-NN method), Bayesian inference. I have a solid background in simulation methods, the computational aspects are important topics and I am interested in the development and implementation of optimization techniques and algorithms for stochastic complex systems. I am also interested in the logical and philosophical foundations of statistical inference and probability theory.
My current research concerns the statistical modelling of environmental complex problems as, for instance, environmental risk assessment, analysis of presence-only data, analysis of over-dispersed counts data, biodiversity assessment. Other relevant topics are related to the analysis and simulation of complex systems, Markov Chain Monte Carlo algorithms, statistical machine learning and data mining.
Keywords

Spatial statistics, Markov random fields, Markov Chain Monte Carlo methods, Bayesian inference, mixture models, optimization, complex systems simulation.