Laurel
Orr

Laurel Orr is a researcher at Numbers Station working on applying generative AI to data tasks. She graduated with a PhD in Databases and Data Management from Paul G Allen School for Computer Science and Engineering at the University of Washington and then was a PostDoc at Stanford working for Chris Ré in the HazyReserach Labs. Her research interests are broadly at the intersection of artificial intelligence, foundation models, and data management. She focuses on how to train, customize, and deploy foundation models to data tasks. This includes problems around data curation and management for RAG systems, efficient model training and inference for batch workloads, and agentic prompting paradigms for high-performant applications.