I'm a Computer Science student at the University of Colorado Boulder and a 2025 Break Through Tech Fellow. My interests lie at the intersection of AI, cloud computing, and full-stack development. I am committed to building technology that creates meaningful impact and improves user experiences at scale.

Currently exploring: machine learning, python, web development Recent experience: Sprintern at Google Cloud In progress: RunHer and app focused on creating a safer running community for women Contact: lizzie.ruff@colorado.edu LinkedIn: www.linkedin.com/in/lizzie-ruff-3609a1230

Below are selected projects that highlight my technical experience and areas of focus:

A full-stack web application designed to help users discover movies, share opinions, and connect through social features like watchlists, posts, comments, and real-time messaging.

• Project Overview: Built a responsive, Instagram-style movie app enabling users to track favorite films, write reviews, and interact with friends.
• Objectives: Enhance movie discovery through community-driven recommendations and provide a safe, engaging space for movie discussion.
• Methodology:
  • Developed the frontend using HTML, CSS and JS and handlebars framework.
  • Implemented the backend using Node.js, Express, and PostgreSQL, with session-based authentication and RESTful API design.
  • Enabled real-time chat with Socket.IO and integrated secure image uploads via multer.
• Key Features:
  • Watchlist management and post feed with public/private visibility
  • Follow/unfollow system with approval notifications
  • Commenting, liking, and messaging between users

A simplified, C++-based version control system inspired by Git, designed to help users manage file changes locally through a custom set of core commands.

• Project Overview: Built a command-line tool that supports essential version control operations such as init, add, remove, commit, and checkout, simulating core Git functionality.
• Objectives: Gain a deeper understanding of file versioning systems, dynamic memory management, and data structures through hands-on implementation of a minimal Git-like system.
• Methodology:
  • Implemented core data structures:
    • Doubly linked list for tracking commit history.
    • Singly linked list to manage files within each commit.
    • Hash table for storing and retrieving commit metadata efficiently.
  • Designed file system interactions to track modified files and generate versioned snapshots.
• Key Features:
  • Version control operations: add, remove, commit, checkout, and init
  • printLog to visualize commit history
  • search and help commands for enhanced usability