معرفی
Marta Blangiardo is a Professor of Biostatistics and Chair in Biostatistics at Imperial College London's Department of Epidemiology and Biostatistics (School of Public Health). She leads the Biostatistics and Data Science theme at the MRC Centre for Environment and Health. Her research focuses on spatial/spatio-temporal Bayesian models for environmental exposure estimation and health risk assessment, particularly in air pollution modeling, climate change impacts, and aircraft noise epidemiology. She co-authored the influential book Spatial and Spatio-Temporal Bayesian Models with R-INLA and collaborates with the Alan Turing Institute on pandemic surveillance.
Education:
- High School Diploma: Liceo Classico "P. D'Anghiera", Arona, Italy (1997)
- MSc in Statistics, Demography and Social Sciences (Summa Cum Laude), University of Milan Bicocca (2001)
- PhD in Applied Statistics, University of Florence (2004)
Research Interests: Her work integrates environmental data with health outcomes, emphasizing methodological innovations in spatial modeling. Key areas include:
- Air pollution exposure estimation using multivariate data fusion
- Assessing cardiovascular risks linked to aircraft noise (ANCO project)
- Climate change effects on respiratory diseases via temperature modeling
- Bayesian hierarchical models for public health surveillance
Recent Contributions: Her team developed frameworks for real-time COVID-19 monitoring using wastewater data and contributed to understanding pandemic mortality patterns across Europe. She also leads projects on pesticide exposure and pancreatic cancer in France, and dengue fever spatiotemporal dynamics in Brazil.
Awards & Grants: While no specific awards are listed, her sustained leadership in environmental biostatistics and multiple high-impact collaborations (e.g., with Public Health England and the Turing Institute) reflect her scholarly impact. She has secured grants for projects like the ANCO study and pandemic surveillance initiatives.
Labs & Teams: Oversees the envstats.org research group focused on environmental statistics and collaborates with the RSS-Turing lab for AI-driven public health analytics.
