Behavioral Head-Tracking
Analysis on Songbirds:
Detecting Unexpected Sounds from Unexpected Sources Using
Modern Computational Methods

Data & Behavioral Research Analyst/Research Assistant

I completed my senior thesis in the Vicario lab, where I led behavioral experiments on 50 songbirds using DeepLabCut to study song learning, auditory discrimination, and spatial attention.

I built and optimized the deep neural network training and evaluation pipelines, cutting training time from 8 to 3.5 hours. I also carried out manual annotation and quality checks that reached over 90% agreement and recovered missing pose data.

Aside from the research, I mentored undergraduate researchers in our lab and was awarded the Henry Rutgers Scholars Award, the Paul Robeson Thesis Scholar distinction, and an Aresty Research Grant.