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Invited Talk: AI-Ready Scientific Workflows at Scale: Bridging Data, Infrastructure, and Automation
DescriptionThe convergence of AI and large-scale scientific workflows presents a transformative opportunity to accelerate discovery across domains. However, this integration is challenged by fragmented data lifecycles, heterogeneous infrastructure, and the need for scalable orchestration frameworks that are both AI- and HPC-aware. In this talk, I will present an end-to-end vision and practical strategies for enabling AI-ready scientific workflows at scale. This includes integrating domain-specific foundation models, automating data staging across distributed resources, and leveraging adaptive workflow systems to optimize performance, cost, and energy usage. Drawing from real-world use cases within DOE science domains, I will outline a community roadmap for building interoperable, scalable, and FAIR-aligned ecosystems that support both traditional simulations and next-generation AI models in federated environments.