Carolyn Qu

Strong academic foundation in human-centered AI and NLP: Carolyn completed a Symbolic Systems undergraduate honors thesis and an MS in Computer Science (AI focus) at Stanford, and produced course-scale research projects (e.g., a CS224N final project on compositional generalization) that combine linguistic/psychological perspectives with modern neural architectures. stanford+2

Balance of teaching, mentorship, and engineering: she has served as an Advising Fellow in Stanford's Symbolic Systems program and as a Course Assistant for CS131, alongside public-facing teaching/content work for Create & Learn—reflecting strengths in mentoring, curriculum-style communication, and translating technical ideas for learners. stanford+2

Hands-on software engineering and product experience across academia and industry: public engineering work (GitHub, Devpost) and listed industry roles (Amazon AGI Autonomy, Jane Street, Apple internships, and currently Unify) show an engineer who moves between research-adjacent AI work and product-focused engineering roles. github+2

Public, developer-focused presence: maintains GitHub repos and a personal GitHub Pages site, and publishes projects and hackathon submissions on Devpost—indicating an emphasis on shipping prototypes, front-end work, and reproducible course/research artifacts. github+2