Research Themes

Computational epidemiology

This research theme focuses on epidemiological analysis and mathematical modeling of the spread of infectious diseases. The goal is to understand the mechanisms of transmission and predict the evolution of epidemic outbreaks, with a focus on emerging and re-emerging viruses such as SARS-CoV-2, Ebola, Mpox, arboviruses.

Molecular phylogenetics and evolutionary dynamics

This research theme explores the genetic and evolutionary history of viruses and other organisms using sequencing technologies and bioinformatics. It aims to reconstruct phylogenetic relationships, track viral mutations, and understand adaptation mechanisms, with applications in infectious disease surveillance.

Artificial intelligence in epidemiology and public health

This research theme explores the application of artificial intelligence (AI) in epidemiology and genomics. It focuses on developing predictive models for epidemics, analyzing big data from genomic and epidemiological sources, and optimizing surveillance and intervention strategies.

Public health risk assessment

This research theme focuses on evaluating health risks associated with infectious diseases, environmental factors, and mass gatherings. It aims to assess outbreak potential, model disease spread, and develop strategies for prevention and mitigation, with applications in pandemic preparedness and global health security.