Python developer building data transformation pipelines, domain modeling, and AI-assisted systems.

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I started studying programming when I realized I could create and iterate far faster by externalizing my thinking into software — instead of relying solely on manual processes and other people's tools.

Previously, I spent 13+ years leading technology innovation projects, IP strategy, and applied research — work that trained me to break down complex, ambiguous problems into structured, testable systems. I'm now applying that same discipline to software: deterministic algorithms, structured data modeling, and explainable AI workflows.

• Full-time, intensive study of Python and software engineering
• Building MonsterForge, a data transformation pipeline combining typed domain modeling, LLM-assisted semantic classification, confidence-gated human review, SQLite/SQLAlchemy persistence, and a separate JSON API (FastAPI + Pydantic), containerized with Docker and tested via GitHub Actions CI on every push — try it live, or browse the public gallery of real output
• Focus areas: ETL pipelines, domain-driven design, REST API design, append-only event logging, human-in-the-loop validation, automated testing

• 13+ years in technology innovation and R&D

• 3 international patents

  (details)

  • Renewable energy
  • Aerospace
  • Batteries

• Multiple national patents

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  • Training equipment
  • Advanced materials

• Cross-domain materials development

  (details)

  • Design
  • Structural
  • Ceramic
  • Sulfide
  • Battery materials

Python · FastAPI · Pydantic · SQLAlchemy/SQLite · SQL · Docker · pytest · Jinja2 · HTML/CSS · Bootstrap · Google Gemini API

Dev environment: Linux (Xubuntu) · Bash/CLI