Amy Yunyu Chiang
I am a research scientist specializing in causal inference, experimental design, and quantitative analysis to drive data-informed decisions for policy, health products, and digital platforms.
About
I am a research scientist specializing in causal inference, experimental design, and quantitative analysis to drive data-informed decisions for policy, health products, and digital platforms.
I have experience leading large-scale studies, building predictive models, and translating complex data into actionable insights for diverse stakeholders. I collaborate with clinicians, researchers, and developers to improve data quality, accelerate delivery, and design user-centered interventions.
- 12 years' experience
- Joined January 2026
Skills· 4
Languages
- EnglishFluent
Industry experience
- Healthcare
- Education
- Professional Services
- Media & Entertainment
- Software & Internet
- Government
- Life Sciences
- Other
More experts in San Francisco, United States
Work experience· 5 roles
Design and execute data-driven strategies to generate actionable insights for diabetes interventions, partnering with cross-institutional stakeholders (Stanford, UCSF, Kaiser) to advance health equity and inform scalable solutions.
Applied computational methods to analyze 108K+ Facebook posts and 1.4K BLM protests, uncovering patterns in social movements and media framing that informed scalable insights for digital engagement strategies.
Led research evaluating social and economic policies on health outcomes and safety net programs; produced 5 publications (4 first author) and actionable insights for NIH/NIMH ($700K) and AHRQ ($1M) projects. Served as analytics lead—providing statistical guidance, dashboards, and training to interdisciplinary teams while mentoring junior analysts to improve data quality and accelerate delivery. Developed interactive R/Shiny apps and novel sequence analyses to visualize COVID-19 policy impacts; optimized trials and usability studies through collaboration with clinicians, researchers, and developers. Analyzed patient EHR data to evaluate treatment protocols, uncovering barriers to uptake and informing design of more user-centered health interventions.
Education
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