Dong Jun Woun

Coursework: Computer Systems Organization, Reinforcement Learning (Python)

Minors: Machine Learning & Cyber Security · Dean’s List (Fall 2020 – May 2024) · Cook Grand Challenge Honors
Coursework: Data Structures & Algorithms (C++), Systems Programming (C), Software Engineering (React, Sass, Python), Intro to ML (Python), Deep Learning (Python), Software Security, Network Security

• Developing & refining features for PAPI (performance monitoring toolkit) in Bash & C.
• Added capability to disable automatic features, enhancing flexibility and user control on macOS.
• Streamlined testing to focus on active hardware, improving efficiency & accuracy.

• Architected CI/CD pipeline for automated hardware‑in‑the‑loop (HITL) testing.
• Built Python/pytest automation framework for diagnostics, log parsing, and HTML reports.
• Deployed reproducible infra with AWS CDK & Docker; designed secure code‑signing framework.

• Achieved 3.5–4.5× speedups by implementing SVM on quantum hardware (Python).
• Scaled on the world’s fastest supercomputer, reaching 11.1× processing speed improvement.
• Authored research on quantum tech in ML (arXiv:2401.12485).

• Built SVM model for simulated quantum computers; benchmarked vs. classical baselines.
• Reached 95.8% accuracy (Iris) and 94.2% (Digits) on classification tasks.