Priya Sandoval

Priya leads Drane Labs' research division with a focus on dataset provenance, training data integrity, and the methodological foundations that make AI systems trustworthy. She holds a PhD in Computational Ethics from MIT, where her dissertation on provenance tracking in large-scale training corpora received the ACM SIGAI Doctoral Dissertation Award.

Before joining Drane Labs, Priya was a senior research scientist at Microsoft Research, where she led the Responsible Data Practices group and co-authored the internal data sourcing guidelines that were eventually adopted company-wide. She also spent two years at the Allen Institute for AI working on dataset documentation standards that became the basis for the now widely-used Datasheet framework.

Priya has been a vocal advocate for industry-wide standards in data sourcing and model transparency, testifying before the Senate Commerce Committee in 2024 on the need for federal dataset disclosure requirements. She believes that responsible AI begins long before the first training run — in the choices made about what data to collect, how to label it, and whose voices are represented.