Ravi Kiran Pagidi, Navy Federal Credit Union , USA

IEEE Senior Member

Bio: Ravi Kiran Pagidi is an AI and Data Systems Researcher and Senior AI Data Engineer with 11+ years of experience in scalable data architectures, intelligent systems, and cloud-native big data platforms. His work spans AI, machine learning, generative AI, agentic AI, and production-ready data systems across both research and enterprise environments. A Senior Member of IEEE, he contributes to the global research community through publications, peer review, and invited Technical Program Committee roles at international conferences. His interests focus on artificial intelligence, generative AI, big data engineering, data analytics, and data-driven intelligent systems.

Title: From Big Data to Intelligent Learning: Designing Production-Ready Generative AI Systems for Education
Abstract: Generative AI is rapidly transforming digital education by enabling personalised learning, intelligent tutoring, automated content support, and real-time academic assistance. However, moving from experimental prototypes to production-ready educational AI systems requires far more than model selection. It demands robust big data foundations, scalable architectures, reliable pipelines, governance controls, and continuous monitoring to ensure quality, trust, and operational sustainability.
This presentation explores how big data engineering principles can be used to design production-ready generative AI systems for education that are scalable, secure, and aligned with real-world institutional needs. Drawing on reference architectures, case study evidence, and operational lessons from deployments, it provides a practical blueprint for institutions and EdTech platforms ready to move from pilot to production.