Active Projects
-
LUCID: Low-Dose Understanding, Cellular Insights, and Molecular Discoveries
A DOE-funded research project integrating experimental radiation biology, artificial intelligence and machine learning, bioinformatics, and large-scale computing to determine how low-dose ionizing radiation alters cellular and molecular processes. The project develops interpretable methods and reusable computational workflows for analyzing genomic instability, gene-expression pathways, mutational signatures, longitudinal cell morphology, and relationships between molecular changes and observable cellular phenotypes.
-
ModCon: Transformational AI Models Consortium
A DOE-led consortium that accelerates the development of next-generation scientific AI models through shared infrastructure, standardized data practices, and collaborative AI capabilities. It provides AI-ready data pipelines, reproducible scientific workflows, baseline AI technologies, partnership frameworks, and evaluation standards while working closely with the American Science Cloud (AmSC). By reducing duplication and enabling reusable capabilities across domains, ModCon empowers researchers to develop robust, multimodal, and trustworthy AI models that accelerate scientific discovery.
-
PESO: Partnering for Scientific-Software Ecosystem Opportunities
A DOE initiative that advances the scientific software ecosystem by coordinating software stewardship, integration, quality, sustainability, and community engagement across DOE-funded software projects. Working closely with the Consortium for the Advancement of Scientific Software (CASS), PESO improves the usability, reliability, and long-term impact of scientific software through ecosystem-wide collaboration.