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AI is reshaping how hyperscale infrastructure is planned, built, and operated; yet the intelligence layer driving these decisions remains underexplored in systems research. IILM 2026 brings together researchers and practitioners to advance AI-driven capacity planning, workflow automation, constraint-aware optimization, and platform engineering at scale. The workshop addresses real-world challenges including demand forecasting, anomaly detection, and human-in-the-loop governance for large-scale infrastructure systems. If you've ever wondered how the world's largest infrastructure organizations decide what to build, when to build it, and how to automate it at scale - this is your workshop.
The 3rd workshop on Federated and Privacy-Preserving AI for HPC (FPAI-HPC’26) brings together academia, industry, government, and research laboratories to explore how federated and privacy-preserving AI can be designed, scaled, secured, and deployed across distributed high-performance computing environments. The workshop spans federated foundation models, scalable learning systems, security, scientific computing, sustainable AI, and agentic workflows, connecting foundational advances with practical systems and real-world applications.