AI SYSTEMS · MACHINE LEARNING · COMPUTER ARCHITECTURE

Pei Ling Chang

Computer Science M.S. student and AI systems builder based in Taiwan.

SUMMARY

Computer Science graduate student with hands-on experience building AI applications, research prototypes, backend systems, computer-vision pipelines, and computer-architecture simulations. Experienced with Python, Git, Linux, LLM workflows, technical documentation, and open-source review.

EDUCATION

National Dong Hwa University

M.S. in Computer Science2025–Present
B.S. in Computer Science2018–2025

SELECTED PROJECTS

Neko.exe — Event-Driven AI VTuber

Python · FastAPI · LLM · Live game telemetryActive
  • Built an event-driven pipeline that converts live game events into context-aware AI commentary.
  • Integrated conversation memory, LLM routing, character responses, and runtime outputs for streaming workflows.

PIM-Aware Coherent NoC Research

Computer architecture · NoC · PIM · SimulationResearch direction
  • Investigating congestion onset and adaptive control in coherent on-chip networks for processing-in-memory workloads.
  • Planning a small synthesizable digital PIM primitive to connect system-level study with implementable hardware.

Plant Electrophysiology Modeling

Scientific ML · Time series · SINDyResearch
  • Modeled nonlinear plant electrical signals using latent dynamics, sparse system identification, and external stimulus coupling.
  • Evaluated model stability and topology under noisy conditions.

Figure Skating AI Coach

MediaPipe · DTW · Motion analysisCourse project
  • Built a pose-based motion-analysis and feedback pipeline for figure-skating movements.
  • Designed phase-aware analysis for loading, takeoff, landing, recovery, and exit behavior.

OPEN SOURCE

Cardano Foundation — cardano-org Contributor

Git · GitHub review · Documentation2026
  • Merged PR #705 to update outdated production app-directory links after verifying replacement domains.
  • Merged PR #706 to explain the Net Change Limit governance concept and improve related chart wording.
  • Worked through issue selection, branching, review feedback, revision, and merge.

TECHNICAL SKILLS

Programming: Python, C, C++, Bash

AI / Data: PyTorch, scikit-learn, OpenCV, MediaPipe, LLM workflows, prompt design, model evaluation

Systems: Computer architecture, Network-on-Chip, embedded systems, performance simulation

Tools: Git, GitHub, Linux, WSL, VS Code, FastAPI

LANGUAGES

Mandarin Chinese — Native
English — Professional working proficiency