معرفی
Ana Torralbo is a Senior Research Fellow at the Institute of Health Informatics, University College London, specializing in computational methods for analyzing electronic health records (EHR). She develops scalable disease phenotyping algorithms and collaborates with institutions like the British Heart Foundation Data Science Centre and the CVD-COVID-UK / COVID-IMPACT consortium.
Her research interests focus on the systematic study of human diseases at scale using large EHR cohorts, including UK Biobank and Genes & Health. She works on improving disease risk prediction, understanding pandemics' impact on comorbid populations, and validating reproducible phenotyping frameworks.
Torralbo leads computational pipelines for the Disease Atlas and co-investigates the GSK-UCL Phenomics Hub. She supervises postdoctoral data scientists, dissertation projects, and internships, while teaching modules like Principles of Health Data Science and Advanced Statistics for Records Research at UCL.
- Scientific Awards: Marie Curie Research Fellowship
Her work spans biomedical informatics, epidemiology, and statistical data science, with recent publications on proteomic biomarkers, disease phenotyping frameworks, and pandemic mortality disparities. She integrates computational statistics into public health research, emphasizing reproducibility and national health data systems.
