I turn ambiguous testing problems into repeatable workflows, measurable engineering evidence, and practical AI-assisted tools.

My background combines product validation, requirement discovery, user-centered thinking, project management, hands-on engineering tool development, and applied Generative AI.

• AI Enablement & Workflow Design
• AI-assisted Engineering Tool Development
• Workflow Automation
• QA / Product Validation
• Requirement Discovery & System Analysis
• Human-in-the-loop Validation
• Engineering Evidence & Reporting
• UI/UX for Engineering Tools

Understand the problem → Define the evidence → Break down requirements → Build a prototype → Validate with real devices → Refine

I use AI as a development and problem-solving partner, not as a source of ground truth.

My workflow combines structured problem decomposition, cross-model review, domain feedback, deterministic logic, real-device testing, and iterative UI/UX refinement.

Vendor-neutral Windows engineering tool for repeatable Effective CPI measurement using native Windows Raw Input and a known physical travel distance.

What it evaluates

Accuracy · Repeatability / CPI CV · Path Quality · Relative DPI Scaling · DPI-group evidence

Engineering workflow

Configure → Capture → Analyze → Structured JSON / HTML Report

Engineering characteristics

• Native Windows Raw Input
• Per-device measurement evidence
• Explicit measurement geometry and acceptance criteria
• Multi-trial repeatability analysis
• Fail-closed capture / admission behavior
• Source installation workflow for clean Windows environments
• Security, public-data, and release documentation

Current public release: v0.1.0rc2 Source Release Candidate

My role

Requirement Discovery · Measurement Methodology · Architecture · AI-assisted Development · UI/UX · Testing · Release Validation

Independent Windows QA tool for converting raw mouse click behavior into measurable and reviewable engineering evidence.

What it measures

Click Timing · Hold Duration · Cadence · Chatter / Bounce · Missed / Extra Events · DUT vs Setup Behavior

Engineering workflow

Windows Raw Input → Event Capture → Deterministic Analysis → Visualization → Structured Report

My role

Requirement Discovery · QA Methodology · AI-assisted Development · UI/UX · Synthetic & Real-device Validation

Public release: v1.0.0

Engineering
Python · PySide6 · Windows Raw Input · pytest · Git / GitHub · JSON / HTML Reporting

AI-assisted Development
ChatGPT · Google Gemini · Cursor

QA / Validation
Platform Compatibility · Functional Testing · User Scenario Testing · USB / Peripheral Validation

Design / Visualization
Figma · Information Visualization

Project Management
Project Management Professional (PMP)

Power Cycle Validation
Workflow automation for unattended power-cycle testing, failure tracking, device enumeration checks, functional verification, and structured reporting.

AI Test Requirement Assistant
Exploring structured requirement discovery, clarification workflows, and AI-assisted test planning with human review.

The projects presented here are independent personal work.

Public materials use my own environment, public technical documentation, commercially available products, or synthetic examples.

No confidential employer information, unreleased product specifications, internal source code, or proprietary test data is published here.

I'm interested in opportunities around:

AI Enablement · Workflow Automation · Engineering Tools · QA Automation

My goal is to help teams move AI beyond simple Q&A and turn it into practical, reviewable workflows that improve how people work.