Hi, I'm Elizabeth and I'm a Junior at Cornell University studying Computer Science in the College of Engineering. Originally from Redmond, Washington, I'm passionate about software engineering, machine learning, system design, and algorithmic design.
I have experience across both front-end and back-end development, and I take pride in my attention to detail and thoughtful approach to building reliable, well-designed systems. I enjoy tackling complex problems and continuously expanding my technical skill set, whether by exploring new technologies or deepening my understanding of core concepts. I’m especially interested in applying my technical background to real-world challenges and finding creative ways to merge my interests with technology.
Outside of coding, you'll usually find me watching or playing amateur tennis, going on nature walks, traveling, or spending an embarrassing amount of time on social media. All the photos featured on this site were taken by me.
Incoming this fall on Google Photos Team
Incoming this summer on Signal Growth Team
Developed a full-stack feature for YouTube Music’s in-app lyrics on Android and iOS, used by tens of millions of listeners worldwide, and successfully launched it to production.
Implemented a full-stack feature for an internal experiment launch tool by extracting data from the tool’s metamodels using Java and a Google internal configuration language.
Hackathon project that scrapes open source projects using agentic AI to read through repo and suggest fixes.
Our project helps users understand and guide them along the process of fixing GitHub repo issues. The client pastes the link of an issue they're working on, and we use agent orchestration to process the repository and the specific files that the issue targets. Our system collects data persistently through Letta's MemGPT technology and synthesizes information in an interactive and easy-to-grok format for users. The structured and specific data can greatly benefit developers new to the project.
Used a voice dataset to train a model to detect different breathing-related illnesses and stress levels to optimize emergency waiting room queues.
This project helps users understand and guide them along the process of optimizing emergency room operations. The system analyzes patient flow, wait times, and staff workload to provide actionable insights. Our system collects data persistently and synthesizes information in an interactive and easy-to-grok format for users. The structured and specific data can greatly benefit hospital administrators and staff.
Uses OpenCV to analyze hands and estimate measurements for patients with lymphedma to help patients get at-home treatment and monitoring.
The KnitDema project is an innovative application designed to assist people with lipedema or other dexterity-affecting conditions to access at-home, readily-available treatment through a specially-molded glove. The glove is equipped with sensors that can detect the user's hand movements and gestures, which are then processed by a machine learning model to provide real-time feedback and guidance on performing lymphatic drainage massage techniques effectively. The software component of this system ensures users have a easy and seamless experience connecting the glove to the app to access the different treatment modules via bluetooth. The system also integrates computer vision to measure patient hand dimensions and automatically generate a custom glove bitmap for the knitters to use, rather than having the patients come to the lab to get their hands measured. The overall goal of this project is to make the treatment more accessible and personalized for patients, while also providing valuable data researchers using computer vision to efficiently and accurately measure hand dimensions for custom glove generation.
Developed and deployed a full stack feature on YouTube Music that translates song lyrics in real time using the Google Translate API.
The Youtube Music Lyrics Translation project is a mobile application designed to provide real-time translation of song lyrics for users around the world. The app integrates with the YouTube Music platform to fetch song lyrics and uses the Google Translate API to translate them into the user's preferred language. This project reaches over 100 million users worldwide and has been one of the most requested features on the YouTube Music platform.
Built a rendition of Monopoly in OCaml.
Final project for CS 3110, a course on functional programming using OCaml. The project is to implement a version of Monopoly using purely OCaml. The project is built from scratch, including the game logic, user interface, and all game components. The game supports multiple players and includes features such as property trading, auctions, and chance/community chest cards. The project demonstrates a strong understanding of functional programming concepts and OCaml syntax, as well as the ability to design and implement a complex system using a purely functional programming language.
Designed and developed a personal website. Built with a custom CSS grid layout, scroll and hover event listener animations.
My personal website is a portfolio that showcases my projects, experience, and leadership roles. The website is built using HTML, CSS, and JavaScript, and is designed to be responsive and visually appealing. The website features a clean and modern design, with a focus on usability and accessibility. It includes sections for about me, experience, projects, and leadership, as well as a contact form for visitors to get in touch with me. The website is hosted on GitHub Pages and is regularly updated with new content and projects.