Research

Cristina's research topics are cluster analysis and classification, focusing on probabilistic distance clustering, model based clustering and classification. Specifically she focuses on cluster flexibility in term of cluster shapes, outlier detection, high dimensional data, categorical and mixed-type data. She also collaborates with experts in different fields: psychology, environmental science, engineering, and transportation.

Furthermore her interests concern:

• Mixture of generalized hyperbolic distributions

• Mixture of contaminated normal distributions

• Outlier detection

• Multiple scaled distributions

• Probabilistic distance clustering