Yao-Wen Hsieh

Yao-Wen Hsieh

Electrical and Computer Engineering graduate student working across control, sensing, and applied AI.

My work includes first-author research, multi-sensor system development, and industrial PCB vision inspection. I use projects to examine how models, sensors, and physical systems behave under test.

View engineering workOpen résumé
Education
USC M.S. ECE
Expected Summer 2028
Research
2 first-author papers
Controls and sensor fusion
Industry
PCB vision inspection
Trained and tuned inspection models
Focus
Control · Sensing · AI
Open to adjacent ECE roles

Selected engineering work

Three projects showing how I define a problem, own part of the system, and validate the result.

Sensor fusion · Research

IEEE ICCE-Taiwan 2025

Multi-Sensor Waste Classification

Undergraduate capstone. Added light-transmittance and metal sensing to a YOLOv8 camera classifier and fused the four signals with fuzzy logic.

Contribution
Led a 3-person team. Designed the system architecture and module integration, proposed fuzzy fusion, built the photoresistor sensor, co-built the YOLOv8 model, and wrote the paper.
Evidence
120 test passes on unseen items · 63.33% vision only → 90% fused · glass 8/30 → 24/30
  • YOLOv8
  • Arduino
  • Photoresistor sensing
  • Fuzzy logic
  • Sensor fusion

Project lead

First Author & Presenter

Capstone Excellence Prize

View project

Control & dynamics · Research

Accepted to IFAC 2026

Quadrotor Trajectory Tracking

Extended a prior SO(3) sliding-mode controller for multirotors from asymptotic to finite-time convergence of position and attitude tracking errors.

Contribution
Derived the control laws and stability analysis, built the MATLAB/Simulink simulation, and wrote the paper as first author. Also ran the controller in PX4 software-in-the-loop simulation with Gazebo and ROS 2.
Evidence
Figure-eight tracking in nominal simulation · finite-time convergence of position and attitude errors · trajectory and error plots from the paper
  • MATLAB/Simulink
  • Sliding-mode control
  • SO(3)
  • PX4
  • Gazebo
  • ROS 2

Research Assistant

First Author

View project

Industrial vision · Internship

Solomon Technology · 2024

Industrial AI Vision Inspection

Built a PCB inspection demo for Automation Taipei 2024 that checks soldered boards for component placement, wrong components, and solder condition.

Contribution
Set up the camera and lighting rig, collected and labeled the images, trained and tuned the models in Solomon’s vision platform, tested failure cases, and demonstrated at the expo. Also maintained and retrained the showroom live demo.
Evidence
~200 labeled PCB images · reflection, shadow, and position tests · test recordings from the expo project
  • Camera and lighting setup
  • Image labeling
  • Vision platform training
  • PCB inspection

Field Application Engineer Intern

Automation Taipei 2024

View project

Background

Industry application experience supported by an electrical and computer engineering education.

Experience

Solomon Technology Corporation

Field Application Engineer Intern, Vision Business Unit

  • Built a PCB inspection demo for Automation Taipei 2024: a fixed camera and lighting rig, about 200 labeled images, and models trained in Solomon’s vision platform.
  • Tested the models against reflection, shadow, and position changes, reported failures to the AI engineering team, and demonstrated the system at the expo.
  • Maintained the showroom’s live tablet demo and retrained its model.
Read the case study

Education

University of Southern California

M.S. in Electrical and Computer Engineering, General Program

Expected Summer 2028

Chung Yuan Christian University

B.S. in Electrical Engineering

June 2025