Delivering scalable, trustworthy computational solutions to biomedical science and healthcare challenges.
The Advanced Computing for Health Sciences sectionharnesses Oak Ridge National Laboratory’s expertise in artificial intelligence, data science, modeling and simulation, and high-performance computing to accelerate biomedical discovery and improve human health. Working across biological and data scales — from molecules and cells to individuals and populations — the section develops computational methods, software, and integrated workflows that transform complex biomedical data into actionable knowledge and predictive capabilities.
The Biostatistics and Biomedical Informatics Group, led by Heidi Hanson, develops multimodal AI, biomedical informatics, and statistical methods that integrate health, genomic, clinical-text, imaging, environmental, and population-level data into usable evidence for human health. The group advances computational research across multiple domains, including privacy-enhancing technologies for secure analysis of sensitive data, exposomic approaches that connect environmental exposures with health outcomes, and methods for biological design that couple machine learning with molecular simulation. These efforts support AI-ready data, risk prediction, precision medicine, and public health decision-making.
The Scalable Biomedical Modeling Group, led by John Gounley, creates methods and tools that make distributed and sensitive biomedical data usable, reliable, and impactful at scale. The group advances data curation and interoperability, synthetic data and federated learning, biologically-inspired computing, and high performance and agentic AI workflows that connect data, simulation, learning, and scientific decision-making.
The Multiscale Biomedical Systems Group, led by Narender Singh, develops computational and AI-driven approaches to understand, model, and predict biological systems across scales—from molecules to populations. The group integrates molecular simulations, mechanistic modeling, biomedical imaging, high-performance computing, and multimodal AI to advance biomedical discovery, therapeutic development, digital twins, and predictive medicine.
CONTACT
Anuj J Kapadia
Section Head, Advanced Computing Methods for Health Sciences
