How is NASA Building a People Knowledge Graph with LLMs and Memgraph

Apr
4:00pm
How is NASA Building a People Knowledge Graph with LLMs and Memgraph

By Memgraph
A "People Graph" is NASA's People Analytics Team's proposed solution for identifying subject matter experts, determining who should collaborate on which projects, helping employees upskill effectively, and more. By seamlessly deploying Memgraph on their private AWS network and leveraging S3 storage and EC2 compute environments, they have built an analytics infrastructure that supports the advanced data and AI pipelines powering this project. In this session, they will showcase how they have used Large Language Models (LLMs) to extract insights from unstructured data and developed a "People Graph" that enables graph-based queries for data analysis.
This session will cover:
Secure, programmatic data ingestion into Memgraph from AWS S3 buckets.
Building a skills knowledge graph using LLM-extracted data and querying it for workforce insights.
Future plans, including interfacing with the graph via natural language querying.
Designed for developers, data engineers, and AI practitioners, this session will provide a real-world perspective on deploying graph databases in a cloud environment. Join us as we explore NASA’s architecture, challenges, and future aspirations in building AI-driven knowledge graphs for workforce intelligence.

Speakers

David Meza currently serves as the Branch Chief, People Analytics and Head of Analytics for the NASA’s Office of Human Capital. He previously served as Chief Knowledge Architect at NASA Johnson Space Center (JSC). During his tenure at NASA, he has worked in all aspects of the Information Technology field developing and deploying several IT systems in use at JSC. His desire to improve IT processes and systems lead him to earn a Master’s certificates in Project Management and Six Sigma in addition to becoming a NASA certified Lean Six Sigma Master Black Belt. Mr. Meza is conducting research in People Analytics, Automatic Classification algorithms, entity tagging, topic modeling, data driven visualization and text to graph pipelines. He holds a Master’s in Engineering Management from the University of Houston Clear Lake.

Madison Ostermann is a data scientist and data engineer on NASA’s People Analytics team, where she focuses on modernizing cloud infrastructure and advancing AI capabilities. With a background in computer science and a passion for solving complex data challenges, she applies her expertise in cloud architecture, data engineering, and analytics to advance human capital outcomes and innovation. Outside of NASA, she is pursuing an M.S. in Analytics, continuously expanding her knowledge and deepening her inquiry skills.

Katharine Knott is a data scientist on NASA’s People Analytics team, where she focuses on workforce modeling and modernizing data narratives to drive better human capital solutions. With a background in industrial engineering, an M.B.A. emphasized in data analytics, and a passion for solving complex data challenges, she specializes in not only solving problems but also making data insights accessible and digestible for general users. Katharine applies her expertise in simulation & modeling, data narratives, and workforce analytics to foster human capital innovation and support decision-making.
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