/lɪŋˈɡwɪstɪks ənd eɪ aɪ/

AI Research & Strategy Manager

Madison studies the intersection of AI safety & multilingualism.

Testing the limits of AI.

Listen to my recent interview with Sarah Senk (Cal Poly) and Taiyo Inoue (Cal State) at the California Learning Lab where we discuss the limits of AI translation, what AI safety practices like red-teaming reveal about model guardrails, and why human oversight remains essential.

About

With over a decade of experience in linguistics research and the tech industry, Madison is uniquely positioned to translate complex AI concepts into actionable insights. She earned the U.S. State Department NSLi-y scholarship in 2014 to study Korean in Seoul, South Korea and graduated magna cum laude from Colorado State University with a degree in Linguistics. During her studies, Madison worked as a linguistics research intern, investigating Colorado sociophonetics, and project manager for a leading energy research lab. She applied these research skills in the private sector for six years by managing product marketing workflows, such as technical SEO and sentiment analysis, at B2B SaaS organisations.

In her current role as AI Research & Strategy Manager at Appen, Madison developed Appen’s research program to produce original work on cutting-edge topics in AI and her recent paper on multilingual cultural nuance was accepted for presentation as LSA 2026. She also oversees PR, content marketing, and product marketing to present a holistic, tech-forward brand messaging that aligns with industry trends and Appen’s research outcomes.

Passionate about global AI innovation and community-building, Madison advocates for sustainable and equitable growth in the industry through her research and philanthropy. She volunteers her time as a professional mentor for young women in Ethiopia with the Na’amal Foundation and hosts a monthly Women in AI happy hour in San Francisco.

Publications

  • This paper explores the vulnerability of several top MLLMs across a range of attack types. Results demonstrate ongoing safety risks in state-of-the-art models and propose the question: is the safest response no response?
    Read the paper

  • Accepted at LSA 2026

    This pilot study explores how well leading multilingual LLMs translate culturally nuanced language—like idioms, humor, tone, and local references—across 20+ languages, using real marketing copy as a test case. Phase two is in progress. Read the paper.

  • This research explores adversarial prompting in LLMs, featuring a benchmarking study of leading models across harm categories. Read the paper.

  • This literature review paper explores a research-based approach to AI safety best practices across the AI lifecycle with examples highlighting AI safety in high-risk industries, such as law and medicine. Read the paper.

  • This work introduces CoT reasoning for LLMs featuring an expert case study on how Appen built a mathematical reasoning dataset for a leading technology company. Read the paper.

  • As a linguistics research intern for Dr. Cory Holland at Colorado State University, my work contributed to her publication on Colorado vowels. Read the paper.

  • I implemented a corpus-based approach to analyzing differences in speech patterns between urban and rural speakers. This work on the corpus analysis tool, with preliminary results, was accepted for a poster presentation at the Western Conference on Linguistics (WECOL) in 2017. 

  • I supported Dr. Sangbok Kim in the development of his Anytime Korean language learning solution as a research assistant and auditor. Learn more.

  • Contributing author to The Language of Localization published by XML Press. Read the book.