Kenton Murray
Research Scientist at The Johns Hopkins University
Baltimore, Maryland, United States
Summary
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Rockstar🎓
Top SchoolKenton Murray is a Research Scientist at Johns Hopkins University with 13 years of experience advancing natural language understanding and machine translation, particularly for morphologically rich and low-resource languages. He holds a PhD from Notre Dame and a master’s in Language Technologies from Carnegie Mellon, and combines deep academic research with industry engineering experience at Microsoft, Safaba, and others. His work spans statistical and machine learning approaches to MT, probabilistic graphical models, QA, essay grading, and summarization, and he has contributed practical NLP tooling such as NL-Augmenter transformations for dataset augmentation. As a mentor and instructor he advises graduate students and teaches courses, translating research prototypes into robust implementations. Notably, his background includes focused work on Arabic language technologies and hybrid vision–NLP methods developed during an AI2 internship.
13 years of coding experience
9 years of employment as a software developer
St. Margaret's Episcopal SchoolDoctor of Philosophy - PhD, Computer Science and Engineering, Doctor of Philosophy - PhD, Computer Science and Engineering at University of Notre DameMasters, Computer Science - Language Technologies Institute, Masters, Computer Science - Language Technologies Institute at Carnegie Mellon UniversityBachelors of Science in Engineering, Computer Science, Bachelors of Science in Engineering, Computer Science at Princeton University
Github Skills (6)
text-manipulation10
nlp10
data-augmentation10
python10
natural-language-processing9
testing7
Programming languages (6)
Github contributions (5)
GEM-benchmark/NL-Augmenter
Aug 2021 - Sep 2021
NL-Augmenter 🦎 → 🐍 A Collaborative Repository of Natural Language Transformations
Role in this project:
ML Engineer
ML EngineerContributions:7 reviews, 14 commits, 1 PR in 1 month
Contributions summary:Kenton primarily contributed to the development of natural language transformations within the `nl-augmenter` repository. Their work focused on implementing a "concat" transformation, designed to augment the dataset by concatenating sentences. They further separated the transformation into monolingual and bilingual versions, and also updated the tests. Additionally, the user added keywords to these transformation classes.
nlpinformation-theorysentencedeep-learningmachine-learning
KentonMurray/bevara
Nov 2012 - Nov 2013
Contributions:11 commits in 11 months
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