Chang-Yen (Brian) Li

M.S. Electrical & Computer Engineering (Software Engineering & Systems)

University of Texas at Austin (Aug 2025 - Present)

+1 (737) 398-1736
changyenli2002@gmail.com
BrianLii

Education

University of Texas at Austin Aug 2025 - Present
M.S., Electrical and Computer Engineering – Software Engineering and Systems Track
National Taiwan University Sep 2020 - Jun 2024
B.S., Department of Computer Science and Information Engineering
Overall GPA: 4.26 / 4.3   |   Class Rank: 2 / 145   |   3x Dean's List
Relevant courses: Foundations of AI, Machine Learning, Applied Deep Learning, Algorithm Design and Analysis, Computer Architecture, Operating Systems, Web/Systems Programming, Linear Algebra, Calculus.

Work Experience

Software Engineer in Test Intern Jan 2023 – Jun 2023
Synology Inc.
  • Developed and integrated automated tests for Synology's NAS OS (DSM) web APIs using Python's unittest, improving reliability.
  • Automated daily scans across 10,000+ self-hosted GitLab repositories to optimize storage and alert on key/token rotation, improving risk management.
  • Technologies: Git, Python, GitLab CI/CD, Ansible, PostgreSQL.
Wired Network Administrator Sep 2022 – Jun 2024
National Taiwan University
  • Managed wired network infrastructure for 600+ faculty & students.
  • Automated network configuration and backups for 30+ HP switches, enabling rapid incident recovery.

Open Source & Selected Contributions

Apache Airflow
  • Implemented a SQLAlchemy URL generator for various database hooks.
  • Restored and expanded Asset View filters in the Airflow 3.x UI after the 3.0 transition to improve navigation for large workflows.

Selected Projects

Where to Meet – Full-Stack Social & Event Platform Dec 2024
  • Full-stack web app built with Next.js, PostgreSQL, and Drizzle ORM.
  • Features: authentication, profile management, recommendations, real-time chat, interactive event mapping, public/private access control, responsive UI.

Research Experience

Undergraduate ResearcherSep 2022 – Sep 2023
National Taiwan University
Advisor: Prof. Yun-Nung Chen
  • Integrated k-nearest-neighbor (k-NN) retrieval with seq2seq language models for token-level retrieval to enhance dialogue response generation.
  • Reported up to ~3% improvements on key metrics across two knowledge-intensive conversation datasets; demonstrated robust generalization with minimal tuning.

Awards & Honors

  • 2023 ICPC Asia Taoyuan Regional – Gold Award
  • 2021 ICPC Asia Taipei Regional – Silver Award
  • 2020 ICPC Asia Taipei-Hsinchu Regional – Gold Award
  • Taiwanese Olympiad in Informatics – Ranked 24th in IOI national team selection