Michael Kranzlein

About Me

I'm a computer science Ph.D. candidate at Georgetown, advised by Nathan Schneider. I'm looking for industry opportunities starting summer 2024, including roles like research scientist, machine learning engineer, data scientist, software engineer, or similar. If you'd like to get in touch, feel free to send me a message at mmk119 at georgetown(dot)edu.

My Ph.D. has been focused on developing deep expertise in NLP and machine learning with a computational linguistics bent. It's been fantastic to have worked on a variety of projects at Georgetown, ranging from lexical semantics to L2 English to calibration. And by some strange turn of events, I've even published in the Columbia Law Review.

For the past couple of years, including as a Fritz Family Fellow, my work has focused on the language of legal interpretation. My dissertation follows this thread, exploring the relationship of metalanguage to statutory interpretation in the writings of the U.S. Supreme Court. It also proposes methods for using transformer-based models trained on limited annotations to facilitate diachronic analyses of legal text.

I hold undergraduate degrees in Computer Science and French from Belmont University and an M.S. in Computer Science from Kennesaw State University.

Fritz Family Fellow (Summer 2021–May 2023)

In the summer of 2021, I was honored to be nominated and selected as a Fritz Family Fellow. This fellowship is a collaborative research program at Georgetown that focuses on technology and its impacts on society. My fellowship was renewed in 2022, and I continued my work with Nathan Schneider, Kevin Tobia, and Lisa Singh to develop a first-of-its-kind corpus, CuRIAM, for studying legal metalanguage and statutory interpretation.

Internship at EY (Summer 2019)

I first got to explore my interest in legal NLP during the summer of 2019, where I worked as an AI Science Intern at EY's AI Lab alongside a talented team of research scientists and engineers in Palo Alto, CA. During my time at EY, I researched and prototyped new methods for attention-based information extraction from commercial real estate contracts.

Groups

NERT (Nathan's Excellent Research Team)
GUCL (Georgetown University Computational Linguistics)
Fritz Family Fellows