Research

My research focuses on Machine Learning and Statistical Learning applied to biomedical, health-related and social-science data. I am interested in developing and applying statistical models, machine learning algorithms and data mining methods from both methodological and applied perspectives.

Research interests

Non-parametric and ensemble models

A central part of my research concerns non-parametric and ensemble learning methods, with particular attention to robust modelling strategies for complex data structures.

Survival analysis

I work on statistical and machine learning models for censored data, including ensemble approaches for survival outcomes and biomedical applications.

Clustering and Bayesian approaches

My research includes clustering methods, Bayesian ensemble approaches, robust similarity measures and methods for high-dimensional and complex data.

Biomedical and neuroimaging applications

I collaborate on projects involving neurosciences, neuroimaging, radiomics, neurological diseases and biomedical data analysis.

Social-science and health data

I also apply statistical and computational methods to social-science data, including education, socio-economic topics, health data and questionnaire-based research.

Keywords

Machine learning · Statistical learning · Survival analysis · Ensemble models · Clustering · Bayesian methods · Biomedical statistics · Neuroimaging · Health data · Social-science data