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