Resume

Corey Zhou

Full-Stack AI · Manufacturing Digitalization · Product Quality

Email
[email protected]
GitHub
akaBoyLovesToCode
Projects
Selected work
Location
Xi’an, China

Profile

Professional Summary

Manufacturing quality and full-stack data engineer with hands-on experience in SSD back-end yield improvement, semiconductor failure analysis, manufacturing workflow digitalization, and AI-assisted quality systems. Built Python data tools and full-stack internal platforms for engineering evaluation workflows, and developed a production-style Manufacturing Quality Intelligence Platform combining anomaly detection, evidence-grounded root-cause investigation, structured LLM outputs, and corrective-action validation. Experienced in translating manufacturing problems into reliable software, data analysis, and measurable process improvements.

Career

Professional Experience

Engineer III, Semiconductor Product Optimization

Samsung Electronics · Xi'an, China

2020–Present

Product Quality & Yield Engineering

  • Investigate SSD back-end yield excursions using equipment logs, SSD test logs, fail-code patterns, retest behavior, and manufacturing history.
  • Distinguish false failures from genuine product-quality risks and support OCAP and production-line issue response.
  • Connected process, equipment, material, and screening evidence during multi-factor SSD failure investigations.
  • Supported corrective actions that reduced collected and confirmed FET burnout from 11 ppm to 2 ppm, with p-value < 0.001.
  • Monitor post-action recovery through PPM, yield, recurrence, CPK, and statistical validation, including new-product and mass-production evaluations.

Manufacturing Digitalization & Internal Systems

  • Build Python tools, dashboards, and full-stack workflow systems for engineering evaluation, manufacturing-data visibility, and reporting automation.
  • Developed an authenticated full-stack internal platform for engineering evaluation workflows and manufacturing-data review.
  • Standardized relational product, process-step, failure-code, analysis, and workflow data while reducing repetitive manual reporting.
  • Translated engineering requirements into maintainable workflows with clearer evaluation status and manufacturing evidence.

Earlier Engineering Automation

  • Automated repeated yield analysis, manufacturing-log parsing, measurement extraction, trend visualization, and report preparation with Python.
  • Turned raw test records into structured tables containing product, measurement, test-result, and process context.
  • Introduced reusable inputs, visible errors, and version-controlled changes as personal scripts became shared engineering tools.

Selected work

Selected Evidence

Full-Stack AI · Flagship Platform

Manufacturing Quality Intelligence Platform

Full-stack AI platform for manufacturing anomaly investigation, evidence-grounded RCA, structured output validation, and corrective-action validation.

Manufacturing Digitalization · Internal System

Internal Evaluation Workflow Platform

Full-stack internal platform for manufacturing evaluation workflows, structured process data, authentication, reporting, and engineering collaboration.

Product Quality · Failure Analysis

C-Series M.2 SSD DAS FET Burnout Root Cause Analysis and LI Process Improvement

Multi-factor manufacturing root-cause investigation and corrective-action validation that reduced collected and confirmed burnout from 11 ppm → 2 ppm.

Toolkit

Technical Skills

Languages & Data
Python · TypeScript · JavaScript · SQL · Pandas · Polars · NumPy · Regex
Backend
FastAPI · Flask · SQLAlchemy · REST APIs · JWT · WebSocket
Frontend
React · Vue 3 · ECharts
Databases
PostgreSQL · MySQL
AI & Analytics
LLM integration · Structured outputs · Provider validation · Anomaly detection · Statistical analysis · CPK · p-value analysis · Time-series and defect-trend analysis
Engineering & Delivery
Automated testing · Ruff · Docker · Linux · Nginx · Git · Deployment
Quality Engineering
RCA · OCAP support · Yield analysis · False-fail triage · Corrective-action validation · Defect-trend analysis · Manufacturing quality monitoring

Background

Education

Bachelor of Engineering

Electronic Information Engineering

Xi’an University of Technology2019

Practical details

Languages & Availability

Chinese
Native
English
Professional working proficiency
Korean
Basic
Location
Xi’an, China
Relocation
Open to relocation across China
Notice period
14 days