Caterina Gregorio

Caterina Gregorio

Postdoctoral Researcher
Visiting address: Tomtebodavägen 18 A, 17165 Solna
Postal address: H1 Neurobiologi, vårdvetenskap och samhälle, H1 ARC Medicin Vetrano, 171 77 Stockholm

About me

  • I am a post-doctoral researcher with a background in biostatistics. My research focuses on statistical modelling for chronic illnesses, multimorbidity and ageing, both from a methodological and applied point of view using longitudinal real-world data sources. 

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    • 2020- 2024 PhD in Mathematical Models and Methods in Engineering, Politecnico di Milano,  
    • Italy. Supervisors: F.Ieva, G.Barbati. Thesis: “Toward a dynamic approach to decision-making in chronic illness: a statistical framework using longitudinal real-world data”.
    • 2017-2019 Master's Degree in Statistical Science at the University of Padova, Italy. Thesis: "Recurrent events and competitive risks: survival models for the study of arrhythmogenic cardiomyopathy". (Supervisors: G.Cortese, G.Barbati)
    • 2013-2016 Bachelor's degree in Statistics and Informatics for Business, Finance and 
    • Insurance, University of Trieste, Italy. Thesis: "Clustering Algorithms in the 
    • Context of Spatial Big Data". (Supervisor: G.Schoier)

     

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Research

    • Multi-state models and microsimulation.
    • Longitudinal models for repeated measures and latent outcomes.
    • Functional data analysis.
    • Joint models, landmarking.
    • Causal inference,  
    • structural marginal models.

Teaching

  • 2024 

  • Karolinska Institutet, Sweden

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    • Biostatistics I- Master of Public Health Sciences

     

  • 2021-2023 Politecnico di Milano, Italy. Laboratory activities.

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    • Biostatistics -Master’s course in Computational genomics (2 courses, 24 hours and 60 students each, taught in English)
    • Statistics- Bachelor’s course in Mathematical Engineering (1 course, 24 hours and 150 students, taught in Italian)

     

  • 2021-2023 University of Trieste, Italy.

    • Statistics- Bacher’s course in economics and business (laboratory activity, 20 hours, 100 students, taught in Italian)
    • Medical Statistics- Master´s course in data science (lecture, 4 courses, 3 hours each and 10 
    • students, taught in English)

     

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