Research

Cristina's research topics are cluster analysis and classification, focusing on fuzzy clustering, model-based clustering, and classification. Specifically, she focuses on cluster flexibility in terms 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

• Missing data

• Multiple scaled distributions

•Fuzzy clustering 

• Spectral clustering