Simulation Process & Data Management Community Meeting

Reshaping Simulation Data for an AI Future

Thursday 30th April 2026 | Online

The convergence of High-Performance Computing (HPC) and Artificial Intelligence (AI) is revolutionizing engineering simulation, marking the dawn of a data-centric era in innovation and optimization. This paper proposes a comprehensive framework for simulation data management tailored to harness the power of AI for engineering applications. The ability to efficiently manage, analyse, and extract insights from high-quality simulation data is pivotal to realizing the transformative potential of this convergence.

Central to the proposed approach is the establishment of a centralized data repository, designed to unify diverse datasets, including experimental data, numerical simulations, and third-party resources. Such a repository serves as the foundation for streamlined data organization and access, enabling engineers to manage the growing complexity of simulation data effectively. Leveraging AI-powered analytics, advanced machine learning and deep learning algorithms can be applied to these datasets to identify patterns, uncover insights, and drive data-driven decision-making. This capability significantly accelerates the design and optimization processes while reducing reliance on trial-and-error methodologies.

The integration of cloud-based HPC offers a flexible and cost-effective computing solution, enabling engineers to scale resources dynamically based on project demands. This ensures optimal utilization of computational power while maintaining cost-efficiency. Moreover, cloud-based storage provides scalable solutions for managing large simulation datasets, ensuring secure, centralized access for global teams.

By adopting this data-centric strategy, industries such as automotive, high tech, life sciences, and manufacturing can unlock the full potential of AI to accelerate innovation, improve product performance, and reduce development costs. This framework exemplifies the synergistic possibilities at the intersection of AI, HPC, and engineering simulation, paving the way for a transformative future in digital engineering.

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A​bout the presenter

Navin Bagga

I specialize in translating complex engineering and scientific workloads—such as CFD, FEA, and EDA—into scalable Cloud and HPC solutions. Working across AWS, Azure, GCP, and OCI, I bridge the gap between R&D requirements and platform architecture for high-stakes industries like aerospace, automotive, and defence. My focus is on de-risking technical decisions and ensuring engineering teams are fully operational on platform before transitioning to long-term growth.