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