CS graduate who fell in love with programming in high school and took a long winding road back — through freight startups, automotive diagnostics, and everything in between. Education and diabetes care are causes that are deeply personal to me.
My focus is product-minded software engineering: building useful tools while deepening my backend and systems foundations, with a long-term direction in applied AI and intelligent applications.
Open to software engineering roles, especially backend-focused work.
Seven AI skills I use for coursework, with separate roles for course planning, teaching, assessment, research, and build review. Course records preserve plans, assignments, and results across sessions.
Faculty grew out of my experiments with GeminiSensei: I shifted from building a standalone tutoring app toward designing the learning workflow I actually use. The repository documents its workflow checks and limitations.
These projects are complete and archived. Their code, checks, and retrospectives preserve what I built and learned.
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Desktop application · AI tutoring An AI tutoring desktop experiment spanning Tauri, React, and a Python/FastAPI sidecar. Connecting the frontend and backend, managing persistence, and evaluating the full learning workflow shaped my next approach. |
Python · C++ · C# Handwritten neural networks with seeded demos and focused regression checks. A compact exercise in forward propagation, backpropagation, and numerical validation. |
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MCP · Semantic memory A Python MCP and semantic-memory prototype for recording configuration decisions. It taught me to define tools around recurring needs and compare their maintenance cost with a simpler workflow. |
LoRA · Model adaptation A notebook exploring LoRA and 4-bit model adaptation for code generation. Published artifacts, with methodology and reproducibility limits documented; no demonstrated improvement over the base model. |
Languages
Applications and tooling
AI experiments
