I am a full-stack engineer focused on designing and building cloud-native, end-to-end systems—from scalable backend services, modern web and mobile interfaces to production-ready AI models deployed in the cloud. My work spans system and solution architecture, full-stack web development, cross-platform mobile applications, and applied machine learning. I build reliable, high-performance systems using modern frontend frameworks, backend APIs, and cloud infrastructure, with AI models trained, evaluated, and integrated where they add real value. I prioritize clean architecture, performance, and maintainability, delivering systems that are both technically robust and user-focused.
- 📧 Email: mianmhuzaifa@gmail.com
- 📱 Phone: +92 308 6142627
- 🔗 LinkedIn: muhammadhuzaifa
- 🔗 Portfolio: portfolio
Languages: Python, Java, C++, C, Dart, JavaScript, TypeScript
Frameworks & Libraries: Flutter, React.js, Next.js, Node.js, Flask, Retrofit, Material Components, Tailwind CSS
ML Libraries: TensorFlow, Keras, PyTorch, scikit-learn
Tools & Platforms: Android Studio, Visual Studio Code, Visual Studio Community, Jupyter Notebook, Google Colab, Git, AWS(EC2, Lambda, S3, DynamoDB, IAM), Vercel, Render
Databases: Firebase (Realtime Database, Storage), MySQL, PostgreSQL, SQLite, DynamoDB, Redis, Oracle Object Storage
Tools & Platforms: Android Studio, VS Code, Jupyter, Google Colab, AWS (Lambda, EC2, S3), Git
Computer Science Fundamentals: Object-Oriented Programming, Data Structures & Algorithms, Database Systems, Mobile Application Development, Artificial Intelligence, Big Data Analysis, Data Science
- ✅ AI Python for Beginners – DeepLearning.ai (May 2025)
- ✅ Python for Data Science – Udemy (June 2025)
- ✅ Build MakeMore (by Andrej Karpathy) – Self-study (June 2025)
Academic Android app for UCP students with past papers, GPA tools, and assessment tracking. Built with Firebase, MVVM, and SharedPreferences.
Android app that predicts handwritten digits via CNN model hosted on AWS using Flask. Real-time predictions with MNIST-trained model.
Match-3,4,5 puzzle game with combo logic, colorful terminal display, and dynamic scoring. Uses 2D arrays, LinkedLists, and Queues.
A reading and publishing app for public domain books with offline support, reviews, and educational content. It is built with a clean Android UI.
Animated circular clock as a live wallpaper and widget with rotating ticks and real-time digital time. Built using Canvas and custom views.
Image super-resolution tool using ESRGAN/Real-ESRGAN. Supports 2x–16x enhancement with DIV2K training, CLI-based workflow.
IoT-based mobile app that unlocks a Windows PC via Raspberry Pi and fingerprint-authenticated HTTPS requests.
Smart scanner with AI edge detection, auto enhancement, and OCR (Tesseract/EasyOCR). Exports to image/PDF.
Handwriting synthesis tool that mimics real handwriting using AI. Learns from samples and generates styled handwritten text.
AI-powered mobile app for early skin cancer detection using CNNs (VGG, ResNet, etc.) and Flutter+Flask deployment.
PySpark project for classifying product review sentiment using tokenized data, labeled by star ratings, and trained via Spark MLlib.
Always learning. Always building.