About
LABORA — the Laboratory of Artificial Intelligence, Biomodeling, and Outbreak Response Analysis — is a research group at the Escola de Matemática Aplicada (EMAp), Fundação Getúlio Vargas (FGV), based in Rio de Janeiro.
We work at the intersection of applied mathematics, artificial intelligence, and public health, developing methods and tools to understand, predict, and respond to infectious disease dynamics and broader health system challenges. Our approach combines mathematical and computational modeling — agent-based models, causal inference, machine learning with statistical guarantees, population genomics — with close, sustained partnerships with the institutions that put this work into practice: ministries, state health secretariats, hospitals, and public health surveillance systems.
What we do
LABORA's research spans:
- Epidemiological and biosocial modeling — building agent-based models that link individual disease dynamics to social and institutional structure, to evaluate public health interventions before and during their deployment.
- Genomics and evolutionary dynamics — integrating population genomics and landscape genetics with mathematical models of pathogen and vector evolution, connecting genomic signals of adaptation to transmission risk and control strategies.
- Machine learning with formal guarantees — developing methods (conformal prediction, causal regression bounds, prediction-powered inference) that bring statistical rigor to machine learning models used in health and policy decisions.
- Health data and NLP — extracting structured, actionable information from unstructured medical records and administrative health data to support real-time surveillance and clinical decision-making.
- Outbreak and pandemic preparedness — designing tools and protocols for syndromic surveillance, evolutionary and transmission dynamics, and rapid response to emerging health threats.
How we work
Our research is built through long-term, hands-on partnerships rather than one-off consulting: we work directly inside the institutions our tools are meant to serve, testing models against real data and real decisions. Current and past collaborators include the Ministério da Saúde, the Secretaria de Estado de Saúde do Rio de Janeiro (SES-RJ), the Grupo Hospitalar Conceição (GHC), Fiocruz, and research groups at USP, Unicamp, and UFRJ, among others.
LABORA also anchors CIASP (Centro Nacional de Inteligência Artificial para Saúde Pública), a national-scale initiative applying AI to public health challenges across Brazil, spanning medical record analysis, syndromic surveillance, oncology patient navigation, and evidence standardization for health policy.