I am researcher, data scientist, and Georgia Tech MSCS alumna. My areas of focus include: NLP, machine learning, and graphical modeling for the purpose of: (1) multi-modal information extraction and reconciliation; and (2) the development of explainable, hierarchical predictive models, in which micro-level behaviors influence, and are influenced by, macro-level trends.
I am particularly interested in how computational methods and distributed systems can be used to analyze and solve coordination problems and market failures, and/or identify optimal corrective interventions. This problem space is exciting to me because it combines several research areas that I am passionate about, and have experience working on in both academic and professional settings, including computer science, microeconomics, public health, computational linguistics, and spatiotemporal modeling.
Things that make life better (for me) include: open data, reproducible research, coffee, cats, long-distance running, learning new languages, and podcasts.
MS in Computer Science, 2018
Georgia Institute of Technology
An open-source NLP framework for clinical phenotyping.
An Ethereum-based prototype platform to facilitate patient-directed provider-to-provider record sharing.
PyTorch-based pipeline to use CNNs to detect and localize the 14 thoracic pathologies present in the NIH Chest X-ray dataset.