Hammad Ali

Available to hire

I'm Hammad Ali, a Full Stack Developer, AI Engineer, and Python Web Developer with hands-on experience building AI-driven systems, backend services, and production-ready web applications.

About

I’m Hammad Ali, a Full Stack Developer, AI Engineer, and Python Web Developer with hands-on experience building AI-driven systems, backend services, and production-ready web applications.

I have a strong background in machine learning, NLP, Flask-based APIs, and database-driven systems, and I focus on practical, scalable solutions for education, business automation, and industry workflows.

Industry experience

  • Education
  • Healthcare
  • Software & Internet
  • Computers & Electronics
  • Professional Services

Projects · 4

ElderLink is a health and safety platform for elderly users and caregivers. Flutter mobile app with panic button, medicine reminders, health monitoring, and optional smartwatch-style UI. Node.js/Express backend with MongoDB; admin dashboard for staff, roles, and logs. Built with Flutter, Dart, Node.js, Express, MongoDB, and REST APIs.

Current capabilities (high level)
Backend

Elders, medicines, readings, heart alerts, music sessions
Strict MongoDB ObjectId handling and elder resolution for API calls
Medicine-related persistence and outbox-style event helpers (see backend/models/medicineEvent.js, backend/services/medicineEventOutbox.js)
Mobile (mobile/)

Firebase Authentication for staff (email/password and related flows)
Admin / staff areas: live data, logs, roles, settings
Elders and medicines CRUD against the Node API
Backend connection: host/port stored in app settings (defaults + --dart-define=MOBILE_API_HOST / MOBILE_API_PORT); see mobile/lib/screens/backend_settings_screen.dart
Alerts, music, profile / privacy screens
Watch (watch/)

Radial home: Medicine, Switch (change active resident), Clock, My Info, Music, Settings, Health; panic in the center
Medicine schedule from API; Karachi wall-clock for “today” scheduling
Switch resident: recent residents plus facility list from GET /api/elders merged into device history
Cross-elder banner: if another resident has pending doses today, optional prompt to switch
Heart rate / BP style monitoring UI, readings API, panic flow, music with session reporting (when enabled)

  • Full Stack Developer

Desktop application for real-time weight monitoring and fabric roll ticket generation. Built with React, Electron, and Vite. Connects to weighing indicators via serial port, shows live weight, generates QR-coded tickets, tracks weight history, and supports printing + backups.

Highlights

Realtime weight monitoring + stable value detection
Serial port auto-scan + error handling
Ticket generation with QR codes + print flow
Languages: JavaScript

Features
Desktop Application
Real-time weight monitoring from YH-T7E Weighing Indicator
Auto-scan serial ports with multiple baud rate testing
Stable value detection (5 consecutive readings)
Fabric roll ticket creation with professional layout
QR code generation with all ticket data
Weight history tracking and management
Google Drive integration for data backup
Print functionality with formatted output
Python Serial Connection
Automatic Port Scanning: Scans all available serial ports to find the connected device
Real-time Weight Display: Continuously displays weight readings from the device
Status Monitoring: Detects when the machine is ON, OFF, or disconnected
Configurable Settings: Adjustable baudrate and timeout settings
Robust Error Handling: Graceful handling of connection issues and timeouts

Modern, interactive corporate website showcasing AI services, team profiles, blog content, and career opportunities

Industry/Domain

Technology / AI Services / Corp
This project delivers a corporate website for Vertex AI Tec designed to showcase AI services, team members, blog content, and career opportunities. The goal was to create a modern, interactive user experience using animations and WebGL components while maintaining a clean corporate identity.

The solution is a frontend-only React application featuring multi-page navigation, interactive UI components, and media-rich sections, built with performance-conscious animations using GSAP and lightweight WebGL effects.

Course Craft is an AI-powered educational tool that automates:

CLO–PLO Mapping (Course Learning Outcomes → Program Learning Outcomes)

Bloom’s Taxonomy Classification

Student Achievement Analysis

Built with Python, NLP, and Neo4j, Course Craft reduces course design time from days to minutes, ensuring accuracy, consistency, and accreditation readiness for educators and academic institutions.

🚀 Features

Automated CLO Generation – Extracts CLOs from course descriptions and lecture outlines.

PLO Mapping Engine – Uses NLP to match CLOs with relevant PLOs based on curriculum standards.

Bloom’s Taxonomy Classification – Categorizes CLOs into cognitive levels (Remember → Create).

Dynamic Achievement Calculation – Supports variable student datasets for CLO success rate analysis.

Interactive Web Interface – Easy to use via Flask or Streamlit.

Data Visualization – Displays CLO–PLO mappings and achievement rates in clear tables & charts.

🛠️ Tech Stack

Programming Language: Python

Frameworks: Flask / Streamlit

NLP Tools: HuggingFace Transformers, NLTK, BERT

Database: Neo4j (for relationship mapping)

Data Processing: Pandas, NumPy

Visualization: Matplotlib, Plotly

Work experience· 8 roles

Freelance Full Stack Developer · Self-Employed / RemoteSep 2025 – Present · 1 yr 3 mos

Delivered React-based frontend and backend services using Python and Java for small businesses and individual clients; built responsive UI, RESTful APIs, authentication flows, CRUD dashboards, and client-ready features. Collaborated with clients to gather requirements and deliver features incrementally.

Full Stack Developer · Self-Employed / RemoteSep 2025 – Present · 1 yr 3 mos

Delivered React-based frontend applications and backend services using Python and Java for small businesses and individual clients. Built responsive UI components in React, handled API integration and basic client-side validation. Developed and integrated RESTful APIs via Python (Flask) and supported Java-based backend services. Implemented authentication flows, CRUD dashboards, and collaborated with clients to gather requirements and deliver features incrementally. Deployed and tested applications, handling basic server setup and debugging. Used Git/GitHub for version control and iterative development.

AI EngineerJan 2025 – Aug 2025 · 8 mos

Developed a conversational chatbot using AIML for educational and service-based interactions, integrated with Flask and Neo4j. Built AI-powered platforms for curriculum design, content analysis applying Bloom's Taxonomy, and generated weekly lecture plans with CLOs and PLOs. Created NLP-based systems for automated CLO-PLO mapping using BERT, Bloom's Taxonomy, and Streamlit. Designed and deployed real-time face tracking systems using ESP32-CAM, Python, and servomotors. Developed AI chatbot integrations and automated student CLO performance calculations with data parsing and visualization in Python. Built deep learning models using CNNs for bone fracture detection and created real-time controllable camera systems using MicroPython for surveillance and motion tracking.

Software Engineer · NeuralNestJul 2024 – Aug 2025 · 1 yr 2 mos
Software Engineer (Frontend & Backend) · NeuralNestJul 2024 – Aug 2025 · 1 yr 2 mos
AI EngineerJan 2021 – Aug 2025 · 4 yrs 8 mos
Developer / AI EngineerDec 2019 – Aug 2025 · 5 yrs 9 mos
AI EngineerJan 2019 – Present · 7 yrs 11 mos

Education

Bachelors in Artificial Intelligence · University of Management and Technology2024 – 2025
Grade: 79% · Allied School, Pakistan2030 – 2026
Matriculation · Apex College, Pakistan2030 – 2021

Certifications and awards

AI Engineer2021 – 2025

Testimonials · 5.0 from 2 reviews

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