About this Webinar

The semiconductor industry is transitioning from AI copilots to agentic systems capable of orchestrating decisions across design, fabrication, and test. Yet autonomous manufacturing remains constrained by fragmented data infrastructure. Critical datasets are siloed across EDA, MES, inspection, and test systems, limiting real-time reasoning, increasing data movement overhead, and underutilizing GPU-accelerated workflows.

In this webinar, Dr. Janhavi Giri, NetApp, defines the architectural shift required to enable AI factory-scale operations, including unified data access, standardized metadata, and compute – data locality. She  outlines key bottlenecks and proposes a collaborative roadmap across fabrication facilities, EDA vendors, and infrastructure providers to enable scalable, intelligent, and autonomous semiconductor manufacturing.

About the Speaker

Janhavi Giri, PhD
Principal Architect, EDA & AI  
NetApp

Dr. Janhavi Giri is a Principal Architect and Technical Industry Lead for Semiconductor EDA Strategy at NetApp, where she drives the convergence of AI, data infrastructure, and semiconductor workflows. She brings over a decade of experience spanning semiconductor manufacturing, computational lithography, and applied AI/ML, with a focus on enabling scalable, production-grade intelligence across design and fabrication. Dr. Giri is an invited speaker at leading conferences and a recognized voice in AI-driven semiconductor innovation. She collaborates closely with industry consortia, academic institutions, and technology partners to shape next-generation semiconductor ecosystems.