Theses
Thesis Projects
I am available to supervise thesis projects for students enrolled in Statistical and Economic Sciences (Bachelor and Master) and Data Science. My proposals generally involve the development, implementation, or application of advanced statistical methodology to complex data structures.
Research Areas for Thesis Proposals
- Statistical Methods for Genomic Data: Development of models for high-dimensional data, with a focus on microbiome analysis and False Discovery Rate (FDR) control.
- Compositional Data Analysis (CoDa): Theoretical and applied projects involving data that represent parts of a whole (e.g., percentages, proportions) using the Aitchison geometry.
- Ecotoxicological Risk Assessment: Application of robust statistical models and mixture models to assess environmental impact and species sensitivity.
- Environmental and Health Data Analysis: Statistical modeling of environmental time series (e.g., pollen concentrations, climate variables) and their relationship with health outcomes, such as allergic and respiratory conditions.
Technical Requirements & Workflow
Software and Tools
- LaTeX: The use of Overleaf is highly recommended (and often required). It ensures professional typesetting and facilitates the collaborative editing process between student and supervisor.
- R/Python: Students are expected to have a solid foundation in R (preferred) or Python for the computational part of the thesis.
How to Apply
If you are interested in a thesis in one of these areas, please send me an email including:
- A brief description of your interests.
- Your latest transcript of records (Libretto).
- Any specific preference for a theoretical or applied project.
For further information or to discuss a specific idea, please do not hesitate to contact me during office hours.