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Marc Comas-Cufí

Associate professor in Statistics

Universitat de Girona

I am an Associate Professor in Statistics at the University of Girona and a member of the Statistics and Compositional Data Analysis research group.

My research connects statistical methodology with applied collaborations in health, epidemiology, environmental data, and clinical research. I work mainly on compositional and multivariate count data, clustering, survival analysis, competing risks, causal inference, and reproducible statistical workflows.

I teach statistics in undergraduate degrees and machine learning in a Master’s programme in Data Science. I enjoy bringing statistical ideas close to real data problems, both in teaching and in collaborative research.

I am open to consulting and collaborative projects involving statistical modelling, health data analysis, reproducible workflows, and methodological support for applied research.

Research Areas

My research combines statistical methodology, health data analysis, and scientific computing. Current lines of work include:

  • Compositional and multivariate count data. Models and transformations for data constrained by totals, proportions, or component-wise dependence.
  • Health data and epidemiology. Applied work with electronic health records, cardiovascular risk, neurointervention, respiratory outcomes, dementia, and environmental exposures.
  • Survival analysis, competing risks, and causal inference. Methods for longitudinal observational data, treatment effects, event-time outcomes, and risk prediction.
  • Statistical computing. Reproducible workflows, data pipelines, simulation studies, and software-oriented statistical practice.

Selected Talks

CODAWORK 2024

Gaussian zero replacement method for compositional count data sets

SEIO 2023

Model-based zero replacement method for compositional count data sets

IFCS 2023

Clustering count data using compositional methods

V AMYC

A new approach for approximating the parameters of a log-ratio-normal-multinomial distribution

CODAWORK 2022

Clustering count data using compositional methods

Contact

For consulting, research collaborations, or methodological support, feel free to contact me by email.

  • mcomas@imae.udg.edu
  • Campus Montilivi, P-IV Building, Office 255
    17071 Girona
  • Enter building P-IV and take the stairs to office 255 on last floor
  • Telegram Me