Computer Science Student

Andrew Yuan

408-***-**** ***********@*****.*** linkedin.com/in/andrewjyuan github.com/ajyyuan

Education

Carnegie Mellon University, Pittsburgh, PA May 2026 Bachelor of Science, Computer Science GPA: 3.9/4.0 Relevant Coursework: Parallel & Sequential Data Structures & Algorithms, Computer Systems, Functional Programming, Imperative Computation, Theoretical CS, Natural Language Processing, Probability, Inference, Stats & DS Methods Experience

Software Engineer, ScottyLabs, Carnegie Mellon University Jul 2024 – present Tech Team

• Implement a navigation and personalized recommendation app by integrating CMUMaps (an interactive room-level campus map) location data with student schedules and campus dining services using TypeScript, Next.js & Redux

• Build the backend infrastructure for TartanHacks, Pittsburgh’s largest hackathon, ensuring scalability and reliability for over 400 participants using Spring Boot and Kotlin Research Intern, Carnegie Mellon University, under Professor Chad Schafer May 2024 – present Examining Storage-efficient Approximations of 1-D Probability Density Functions

• Developed innovative storage-efficient approximations of probability density functions using Python

• Investigated the efficiency of asymmetric vs symmetric quantile approximations using the Kullback-Leibler Divergence metric to optimize model precision and data storage

• Enhanced the quantile parameterization Python module: improved functionality, boosted computational efficiency 30% Software Engineer, Carnegie Mellon Racing, Carnegie Mellon University Sept 2023 – present Driverless, Perceptions Specialization

• Design and build a fully electric Formula 1 style race car to compete with university Formula SAE teams

• Engineer an efficient alignment and tracking algorithm to enhance the YOLOv5 model using Python/PyTorch

• Built and maintained a GitHub repository to organize data loading, sensor configuration, prediction algorithms, visu- alization tools & testing framework

Projects

Workout Tracker — JavaScript, MERN stack Jul 2024 – Sept 2024

• Built and deployed a full-stack web app for tracking completed workouts using MongoDB, Express, Node.js, and React

• Implemented an API to log various exercises, record sets and reps, and add notes to workouts, along with secure authentication using JSON Web Tokens

Unix Shell — C, POSIX threads Jul 2024 – Aug 2024

• Implemented a basic Unix shell with job control capabilities using a job list to keep track of job statuses

• Applied background and foreground job management, I/O redirection, and handling of signals Astronomy/Machine Learning Research — Python, TensorFlow Aug 2022

• Built a polynomial regression model with a custom cost function using Python/TensorFlow to predict star cluster age

• Awarded 1st Award and IEEE award at the Synopsys Science Fair, competed at the Cal. Science & Engineering Fair Skills

Languages: Python, Java, C, C++, TypeScript, JavaScript, HTML/CSS, SQL, Standard ML, Kotlin, R, MATLAB, Go Libraries/Frameworks: React, React Native, Next.js, Express/Node.js, Mongoose, NumPy, pandas, Matplotlib, Keras Developer Tools: Git, Docker, Vim, VS Code, Appwrite, AWS Awards & Honors

3x Dean’s List High Honors, Carnegie Mellon University 2023 – present 4x USA Physics Olympiad Honorable Mention, Semifinalist 2020 – 2023 4x AIME Qualifier 2020 – 2023

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