I’m a second-year Ph.D. student in the Department of Computer Science at Georgetown, where I work with Dr. Nathan Schneider and his excellent research team—NERT. I work on natural language processing and computational linguistics, and my current research projects are focused on semantic role labeling.
Beyond NLP, I am fascinated by differential privacy, bioinformatics, and new advances in machine learning.
Before coming to Georgetown, I earned undergraduate degrees in Computer Science and French at Belmont University in Nashville and then completed a Master of Science in Computer Science at Kennesaw State University, just north of Atlanta.
If you'd like to get in touch, feel free to send me a message at mmk119 at georgetown(dot)edu.
I was fortunate to spend this past summer in Palo Alto, CA working with a talented team of research scientists and engineers in the AI Lab at Ernst & Young as an AI Science Intern. At EY, I researched and prototyped new methods for information extraction from legal documents.
Master's Thesis: A Multiple Classifier System for Predicting Best-Selling Amazon Products
Kranzlein, Michael (2018) "A Multiple Classifier System for Predicting Best-Selling Amazon Products".
Training on the poles for review sentiment polarity classification
Kranzlein, Michael and Lo, Dan (2017) "Training on the poles for review sentiment polarity classification". 2017 IEEE International Conference on Big Data (Big Data). Boston, MA, 3934-3937.