Yiyang Shao

Yiyang Shao

He/Him/His

About Me

Pronouns: He/Him/His.

I’m Yiyang Shao, a software engineer driven by a passion for tackling real-world problems. With a strong foundation from Duke and NYU, I’ve immersed myself in building high-traffic platforms, AI-powered trading strategies, and innovative algorithms. From boosting user experiences at Zillow to scaling features at IXL, I thrive on solving challenges with curiosity and creativity. I code, create, and aim to make a tangible impact—one solution at a time. 🚀

Education

Duke University

Aug 2022 - May 2024
M.S. in Computer Science; GPA: 3.81

New York University

Sep 2018 – May 2022
B.S. in Computer Science, Honors Mathematics; GPA: 3.85

Languages and Technologies

  • Languages: Python, Javascript, Java, Swift, SQL
  • Technologies: Git, React, Vue, Node, Cypress, Docker, Linux, REST, Pytorch, Pandas, Agile

Professional Experience

IXL | Software Development Engineer

July 2024 – Now

  • Enhanced and maintained robust audio and translation capabilities using Java and React for a high-traffic platform serving 15M+ users globally.
  • Refactored audio and translation components to enhance modularity, scalability, and system simplicity, resulting in improved maintenance and faster integration of new features.

Zillow | Software Development Engineer Intern

May 2023 – Aug 2023

  • Built the final landing page of Zillow Home Loan, handling ~100,000 daily user visits with integrations of pricing, clickstream, and documentation services using React and Python.
  • Boosted third-party leads by 25% by enhancing data security features, improving overall user trust in the home loan website.
  • Contributed to an increase in market share by launching Zillow Home Loan services in New Jersey through full-stack development and seamless deployment.

IFlytek | Core Technology Researcher Intern

May 2020 – Aug 2020

  • Led the development of a high-resolution network, attaining state-of-the-art performance with a 45% MIoU on ADE20K for pixel-level image semantic segmentation tasks.
  • Conducted extensive control experiments with neural networks including ACFnet, OCnet, and Efficientnet.

Selected Projects

GPT-4 based sentiment trading strategy

Sep 2023 - Dec 2023

  • Achieved a PnL of 11.46% and a Sharpe ratio of 0.728 by leading the design and implementation of a GPT-4 based trading strategy for market sentiment analysis.
  • Enhanced model accuracy by 15% and improved scalability by innovating prompt engineering and analytical reasoning.

IOS app development for Gather Green

Feb 2023 – May 2023

  • Developed and launched an iOS shopping app using SwiftUI, creating a user-friendly marketplace interface and an efficient inventory management tool for administrators.
  • Integrated Vapor for backend operations, employing PostgreSQL for robust data handling of product information, user data, and other key details.

Algorithm research on generalized sorting

Mar 2021 – May 2022

  • Innovated a generalized sorting algorithm based on the ELO-rating system, improving performance by 10% over existing algorithms through extensive practical applications.
  • Developed and mathematically proved the optimality and efficiency of a tailored random sorting algorithm specifically for generalized sorting contexts.