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PhilixTheExplorer/README.md

Hey there, I'm Philix (Kaung Hset Hein) 👋

Full-Stack Engineer | Backend Specialist | ML Engineer

I build production-grade systems that scale. My code doesn't just work... it's architected for performance, maintainability, and real-world impact.

🔧 What I Do

I'm obsessed with the details that separate prototypes from production systems. Whether it's optimizing database schemas, building modular API architectures, or deploying ML models at scale, I think deeply about how systems perform under real conditions.

Backend-first thinking: I start with data models, API contracts, and system architecture before touching the frontend. Clean separation of concerns isn't optional... it's how you build systems that last.

ML in production: I don't just train models... I ship them. Inference pipelines, batch processing, error handling, and performance optimization for real-time computer vision and time-series classification.

🚀 Highlighted Projects

Full-stack academic platform with schema-driven architecture, KaTeX math rendering, and Next.js SSR

  • Stack: Next.js, TypeScript, PostgreSQL, Prisma, Docker

GodView AI 🏆 International AI Hackathon 2025 Winner

Real-time patient monitoring system with computer vision and alert integration

  • Stack: FastAPI, YOLOv8, Supabase, Telegram Bot API

End-to-end ML pipeline for multimodal physiological time-series classification

  • Stack: PyTorch, Transformers, healthcare AI, patient-aware data splitting

Production CLI tool with modular architecture and Google Cloud Vision integration

  • Stack: Python, Google Cloud Vision, batch processing, error recovery

High-performance desktop app with memory-efficient mode switching

  • Stack: PyQt6, OpenCV, multi-threaded processing

💡 What Drives Me

The intersection of elegant architecture and measurable impact. I'm fascinated by:

  • How the right database schema transforms query performance
  • Why proper separation of concerns makes codebases maintainable at scale
  • How thoughtful error handling turns prototypes into production systems
  • The challenge of deploying ML models that work reliably in the real world

📫 Let's Connect

Currently seeking opportunities to contribute to engineering teams that value thoughtful architecture, scalability, and continuous learning.

💻 Tech Stack:

LANGUAGES

CSS3 Dart Java HTML5 JavaScript Kotlin LaTeX Markdown Python TypeScript

FRAMEWORKS/LIBRARIES

DaisyUI Express.js FastAPI Flutter JWT MUI NPM NodeJS Nodemon React React Query React Router React Hook Form TailwindCSS Vite

DATABASE/ORM

SQLite Prisma Postgres MySQL MongoDB

DESIGN

Adobe Acrobat Reader Adobe Illustrator Adobe InDesign Canva Adobe XD Adobe Premiere Pro Figma

CI/CD

Git GitLab GitHub

TOOLS

Bitwarden Docker ESLint Notion Postman Prettier Trello


"I don't just write code... I design systems that are robust, efficient, and built to last."

Pinned Loading

  1. SIT-Java SIT-Java Public

    These are the collections of questions and solutions from java course at SIT.

    Java 10 1

  2. bug-gym bug-gym Public

    A lightweight, offline-first Java practice desktop app for beginners. Simulates Moodle-style exam environments with automated testing and syntax highlighting. Built with JavaFX.

    Java 2

  3. ocr_text_extractor ocr_text_extractor Public

    OCR Text Extractor | Myanmar OCR | Google Cloud Vision OCR Service

    Python 6 3

  4. osas_detection_transformer osas_detection_transformer Public

    This project implements a deep learning pipeline for detecting Obstructive Sleep Apnea Syndrome (OSAS) from time-series vital signs and waveform data using transformer architecture. The system proc…

    Jupyter Notebook 2

  5. sit-face-recog sit-face-recog Public

    A real-time Python and PyQt6 desktop app for face recognition and photobooth capture, featuring voice greetings, frame overlays, and optional server-based photo sharing via QR codes.

    Python