Spence Green - CEO at LILT

Spence Green

CEO at LILT

San Francisco, California, United States

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Summary

👤

Senior

🎓

Top School

Spence Green is the CEO and co-founder of Lilt, steering an AI-first platform that blends state-of-the-art NLP with professional translation to make the internet truly multilingual. He holds a PhD from the Stanford AI Lab and brings 13+ years of experience translating deep research in machine translation, mixed-initiative systems, and syntax into production products used by enterprises. His background includes research and published work with Stanford, Google (improvements to Google Translate), Johns Hopkins, and technical diligence at XSeed Capital, evidencing a rare mix of academic rigor and commercial judgment. Early software engineering roles at Northrop Grumman gave him hands-on systems and team leadership experience across defense and large-scale web migrations. An active contributor to the Stanford CoreNLP codebase, he combines low-level code improvements with strategic product vision—driven by the mission to make information accessible regardless of language or origin.

13 years of coding experience

10 years of employment as a software developer

BS Computer Engineering, BS Computer Engineering at University of Virginia

BS Electrical Engineering (transferred to U.Va), BS Electrical Engineering (transferred to U.Va) at Lafayette College

The Westminster Schools

Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Stanford University

Arabic, English

Github Skills (2)

java10

javas10

Programming languages (3)

JavaJavaScriptHTML

Github contributions (5)

stanfordnlp/CoreNLP

Jun 2013 - Apr 2015

CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.

Role in this project:

Back-end Developer

Contributions:890 commits in 1 year 9 months

Contributions summary:Spence focused on improving the `edu/stanford/nlp/process/PTBLexer.java` and `edu/stanford/nlp/trees/EnglishGrammaticalRelations.java` file in the repository. The user made several changes to the code, including removing elements not related to the code. The user's work involved modifying the code in the source files. The code changes are likely related to improving the code structure by correcting several inconsistencies within the files.

word-embeddingssentiment-analysisnatural-language-processingstanford-nlpsuite

stanfordnlp/phrasal

Dec 2012 - Jul 2017

A large-scale statistical machine translation system written in Java.

Contributions:2 releases, 1756 commits, 22 PRs in 4 years 7 months

statistical-machine-translationmachine-translationtranslationstatisticalscale

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