Junky for statistics, experimental methods, and machine learning techniques. It is my passion to generate concise and applied insights from complex, noisy, human-centered data. I am currently seeking opportunities in roles related or adjacent to Quant UX Research, Data Science, Human Factors Research, or relevant Applied Research.

I am a Postdoctoral Fellow and Principal Investigator of the ExCaLBBR Lab. In this role, I lead end-to-end computational social research projects focused on understanding how demographic factors and partisan news consumption influence how people think about and make decisions related to societal concepts such as healthcare and voting. As part of this line of work I leverage NLP and generative LLMs to identify and remove partisan biased language features from large sets of web scraped news articles.

I earned my PhD in Cognitive Neuroscience in 2022 from Carnegie Mellon University where I developed supervised classification models to predict thoughts from high-dimensional brain data. I used unsupervised techniques to uncover language profiles to identify how common meaning of words exist across cultures and languages.