The Biostatistics and Biomedical Informatics Group develops computational methods and AI-enabled tools for biomedical research by leveraging high-performance computing to solve complex, real-world challenges. The group’s interdisciplinary collaborations connect healthcare professionals with specialists in the formal, biological, computational, and physical sciences to ensure the research remains rooted in both innovative discovery and practical application. The group’s tools use multiscale health and environmental data for real-world deployment in healthcare systems and public health operations to enable near-real-time disease diagnosis, surveillance, and treatment. Through its work on synthetic medical data generation and privacy-preserving federated learning, the group has expertise in developing privacy-preserving AI methods. The group has also developed expertise in data curation and AI readiness through its work with heterogeneous health and environmental data. This collection of expertise furthers the group’s mission of providing accurate, actionable insights to detect, track, and mitigate emerging health threats effectively.
Looking forward, the Biostatistics and Biomedical Informatics Group is well positioned to drive innovation at the U.S. Department of Energy. The group’s development of next-generation computational tools will support scientists, clinicians, and public health experts in gaining a more comprehensive understanding of human health and the driving factors that influence disparate health outcomes. The group’s research enables faster, more accurate solutions for disease prevention, personalized treatment, and the safeguarding of individuals and communities from biological and environmental threats. Furthermore, the group’s work goes beyond healthcare to advancing energy resilience and human security. The group offers solutions for handling sensitive information, managing spatiotemporal and time-series data, detecting anomalies, and applying causal ML.
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