furqanagwanPrivate
My personal website and digital portfolio, fully designed and developed from scratch. Features project case studies, a technical blog, and structured MDX-based content—powered by a modern Next.js stack and a custom design system. Content is sourced directly from a private GitHub MDX repository for maximum flexibility and version control.
Creator, Designer & Full-Stack Engineer (2018 – Present)
Achievements
- Designed a custom UI/UX system and implemented responsive layouts
- Integrated dynamic MDX content rendering with category filtering and rich markdown features
- Connected to a private GitHub content repository via API for seamless, version-controlled content updates
- Deployed globally on Vercel with statically generated pages for speed and SEO
Technologies
ReactNext.jsTypeScriptTailwindCSSMDXVercel
furqanagwan-contentPrivate
A private GitHub repository acting as a headless CMS for the furqanagwan website. Stores all MDX files and static images for posts, recipes, and project documentation. Enables simple, version-controlled content updates and easy collaboration via standard GitHub workflows.
Creator & Maintainer (2018 – Present)
Achievements
- Structured content storage using MDX and folders for posts, images, and project data
- Established secure, token-based API access from the website to fetch and render content at build time
- Enabled version control, history, and collaborative editing of all website content using standard GitHub processes
A modern, interpretable AI-powered TDEE and calorie analytics app. Users log daily weight and calorie data, and the backend uses XGBoost (with lagged time series features) to predict real, personalized TDEE values. Built with FastAPI, SQLite, and a CI/CD pipeline for robust, test-driven deployment. Features real-time retraining, advanced feature importance analytics, and full test coverage.
Creator, Designer & AI Engineer (2025 – Present)
Achievements
- Designed and implemented a FastAPI backend with SQLite and full CRUD endpoints for health tracking
- Developed an XGBoost-based model with custom feature engineering (lag, moving average, demographic features) for personalized TDEE prediction
- Automated CI/CD pipeline with >90% code coverage using pytest and GitHub Actions
- Surfaced model feature importances to users, enabling transparency and actionable insights
- Implemented robust test cases for all API branches, reaching near-100% code coverage
- Engineered retraining logic to auto-update models on every new user entry
Technologies
PythonFastAPISQLiteXGBoostscikit-learnPytestGitHub Actions