Hi, I'm David Kartchner
I'm a PhD Student at Georgia Tech
I research natural language processing methods for extracting and synthesizing information from biomedical text to power applications in biomedicine, drug discovery and healthcare. My research at Georgia Tech focuses on active, weakly-supervised, and semi-supervised learning methods for text mining and information extraction with limited to no labeled data.
I currently work with Cassie Mitchell in the Laboratory for Pathology Dynamics. I previsouly completed a MS in Mathematics from Brigham Young University advised by Jeff Humpherys.
I have collaborated with scientists, developers, clinicians, and epidemiologists while working at Enveda Bioscienes, Facebook, GlaxoSmithKline, Recursion Pharmaceuticals, and Intermountain Healthcare.
Featured Research Publications
An AI-assisted interactive tool for creating labeling functions used in weak supervision.
Semi-supervised learning framework for learning for weakly supervised learning
EMNLP (Findings) 2020
A knowledge graph link prediction tool to be used for prediction of novel drugs for COVID-19
An epidemiological study on how air polution -- particularly PM 2.5 -- increases the risk of acute lower respiratory infection.