I’m on the job market. Happy to connect! Personal website: https://www.tonyanguyen.com/ I’m a PhD candidate at UC Berkeley’s School of Information. I study algorithmic systems, focusing on deployments in high-stakes settings, and how to enact human values in system design and AI policy.

Experience

UC Berkeley School of InformationDoctoral Student

2020 — Now

Berkeley, California, United States

UC Dissertation Fellow (2025)

Awarded Meta Research grant; Fairness in Two-Sided Markets: "Community-centered design of school assignment mechanisms for equity" (2022-2023)

Center for Technology, Society, and Policy Fellowship (2021-2022)

NSF GRFP Honorable Mention

MicrosoftPhD Research Intern

2025 — 2025

New York, New York, United States

I led community engagement and participatory workshops to validate how we measure “representational harm” (e.g., stereotyping, omission/erasure) in generative AI. We translated these concepts into a labeling rubric and evaluation schema that teams can operationalize for fine-tuning/SFT data annotation. Outcome: validated, community-grounded criteria and benchmark sets to quantify bias in model outputs and inform policy decisions.