Summary
Evangeline Gao is a PhD student at McGill with a strong foundation in computational neuroscience and medical informatics, combining eight years of research and programming experience with an MS from Yale. She builds end-to-end ML and NLP pipelines for clinical data—having parsed and annotated unstructured EMR notes to train NER models—and has hands-on neurophysiology analysis experience merging spikes and LFPs for population-level inference. Skilled in Python, MATLAB, and tools like spaCy and Prodigy, she translates messy biomedical data into reproducible analyses and visualizations using rigorous statistical testing. Notably, her work has revealed counterintuitive neural attention effects and she has mentored teams and students while teaching intermediate CS concepts. Passionate about applying machine learning to improve health, she seeks roles that bridge computational methods and real-world clinical impact.
7 years of coding experience
4 years of employment as a software developer
High School Diploma, High School Diploma at Lord Byng Secondary
Master of Science - MS, Medical Informatics, Master of Science - MS, Medical Informatics at Yale School of Public Health
Bachelor of Arts - BA, Neuroscience, Bachelor of Arts - BA, Neuroscience at Wellesley College
Doctor of Philosophy - PhD, Epidemiology, Doctor of Philosophy - PhD, Epidemiology at McGill University
Spanish, Chinese, English