I'm a Master's student at The University of California, Berkeley studying Information Management and Systems (MIMS) with a concentration in Data Science. I'm passionate about applying machine learning methods to solve problems involving large amounts of data. I am currently a Teaching Assistant for Berkeley's Information Organization and Retrieval course taught by David Bamman.
I'm currently researching the role of description in fiction. The goal of my research is to to disambiguate critical attitudes towards fictional description using methods from fields like cultural analytics and machine learning. After starting the project in Fall 2021 during Professor Bamman's Applied Natural Language Processing course, I presented my progress at the 2022 Berkeley Digital Humanities Fair. I'm currently continuing this research via an independent study supervised by David.
Prior to grad school, I worked as a Back-End Software Engineer at Brightspot for 2 years. I architected the data pipelines and content solutions for clients like Mattress Firm and Janes. I gained robust experience modeling data, constructing APIs, and collaborating with client stakeholders.
In undergrad, I double-majored in Computer Science and English at The University of Virginia and graduated with High Honors in 2019. My thesis project for the English department, A Digital Analysis of the Lyrical Novel, was advised by Brad Pasanek. Other involvements at UVA include earning a Research Assistant position at The Institute for Advanced Technology in the Humanities (IATH) and assisting with Brad's Puzzle Poetry project.
Most recently, I worked as a Graduate Data Science Intern with Red Ventures. I explored and improved RV's decision optimization API. This exposed me to fascinating areas like reinforcement learning and applied statistics plus gave me a chance to work with massive amounts of data in a fast-paced, real-world setting. I'm looking forward to returning to the team full-time after graduation!