Mei Tan is a software engineer and PhD student at Stanford using AI and NLP to improve teaching and learning, combining a decade of industry-grade engineering with education research. Based in Palo Alto, she brings hands-on full-stack experience from Microsoft Education where she shipped classroom features at scale, led partner integrations, and used clickstream and A/B testing to drive product and architecture decisions. At Stanford GSE she blends computational and qualitative methods to study ed‑tech adoption, co-design with practitioners, and how diverse stakeholders shape ML data specifications. Mei’s background spans embedded systems research, accessibility engineering, and policy-oriented analysis, giving her a rare ability to translate technical design into classroom impact. She mentors and advocates for inclusive practices and accessibility, and is comfortable moving projects from prototypes to reliable, data-informed production.
10 years of coding experience
4 years of employment as a software developer
Bachelor of Arts - BA, Visual and Dramatic Arts, Bachelor of Arts - BA, Visual and Dramatic Arts at Rice University
Master of Science - MS, Education Data Science, Master of Science - MS, Education Data Science at Stanford University Graduate School of Education
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