Langdon Holmes
Applied NLP & machine learning, grounded in psychometric measurement.
The best writers are surprisingly predictable.
I build AI systems for learning, and I measure whether they work. My background combines psychometric measurement (validity, fairness, item response theory), applied NLP research, and the engineering to ship usable + maintainable implementations.
I'm co-founder and CTO of Edumonia, the startup behind the iTELL learning platform, and I'm completing a PhD in cognitive science at Vanderbilt, where my dissertation introduces and evaluates LLM-surprisal as a measure of second-language proficiency.
- 1st place NAEP Automated Math Scoring Challenge, $30k grand prize
- 20+ peer-reviewed publications on NLP, assessment, and learning
- PI on the dataset behind Kaggle's PII Data Detection competition
Projects & Systems
iTELL · co-founder & CTO
A platform that turns course materials into interactive, AI-enhanced texts with comprehension checks, adaptive feedback, and content-aware chat. Deployed with institutional partners as an LTI 1.3 tool inside their learning management systems, running on Kubernetes; learning gains evaluated in a randomized controlled trial. Started as NSF-funded research, now commercialized.
PIILO · creator
An open-source system for deidentifying student writing that makes it easy to use the "hiding in plain sight" obfuscation strategy. As PI on a $30,000 award from The Learning Agency, I built the dataset behind Kaggle's PII Data Detection competition and helped to package the winning submissions into a lightweight, extensible Python package.
Word predictability · dissertation
LLM surprisal as a measure of second-language proficiency. High-proficiency learners make more predictable word choices, and a predictability metric outperformed conventional measures of lexical sophistication in explaining TOEFL score variance. Published in Language Learning.
entroprisal · author
A Python package for information-theoretic n-gram statistics — entropy and surprisal — as measures of text readability. Paper forthcoming.
NAEP automated math scoring · grand prize winner
First place and the $30,000 grand prize in the NAEP Automated Math Scoring Challenge. LLM-based scoring of constructed-response items from the Nation's Report Card, matching human raters closely enough for operational use. Methods published in the International Journal of Artificial Intelligence in Education.
I also designed and maintain my lab's GPU compute cluster, fine-tune speech recognition models for children's voices, and help teach the graduate NLP course at Vanderbilt's Data Science Institute.