My name is Anastassia Kornilova. I am a research scientist at FiscalNote. I spend my days creating insights for legislative and regulatory data using Machine Learning and Natural Language Processing. Recently, I published a paper at ACL on predicting how legislators will vote on bills. In addition to bulding state of the art models, I am, also, interested in figuring out how to best communicate our analysis to users.

Previously, I graduated from Carnegie Mellon University with a Bachelor in Computer Science and a minor in Language Technologies. I’ve, also, interned at Pinterest and Khan Academy.

While my primary work is in teaching machines, I am, also, passionate about education and making technical content more accessible. The purpose of this blog is to bring some of that content to that internet.

I am passionate about teaching humans (and machines) and have given several talks related to my blog posts.

Outside of computers, I love photography, rock climbing and traveling (to both mountains and cities).