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 semi-supervised learning and large language models (LLMs) 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
A comprehensive survey and robustness analysis of biomedical entity linking models for scientific literature
EMNLP
2023
A comparison of the capacity of various LLMs to structure & summarize data from clinical trials and cohort studies
BioNLP
2023
A dataset to filter clinical cohort studies for drug repurposing, pharmacovigilence, and clinical meta-ananalysis
SIGIR
2023
An AI-assisted interactive tool for creating labeling functions used in weak supervision.
AI
2022