abdulhayykhan@portfolio:~

DUET'28 // BS ARTIFICIAL INTELLIGENCE

Abdul Hayy Khan

$ Building production-ready AI systems, backend tools, and practical full-stack products. Passionate about machine learning, agentic workflows, NLP, and architecture that scales.

Public Repositories

50+

Engineering Focus

AI Systems · Backend · Full-Stack

Primary Domain

Artificial Intelligence

git clone profile open linkedin open kaggle send email download cv

~/about/profile.md

about_me()

I'm a BS Artificial Intelligence student at Dawood University of Engineering & Technology (DUET), Karachi, and a developer focused on backend engineering and intelligent systems. I build full-stack tools and agentic workflows that solve real-world problems with practical, measurable impact.

Through internships at FlyRank (ML Engineering), Alkhidmat Foundation (IT), DevelopersHub, and CodeAlpha, I've delivered production systems from emergency-response platforms and content-scoring models to real-time collaboration tools and automated security vaults.

~/focus/areas.json

focus_areas[]

  • > Machine Learning & AI: Content scoring, RAG architectures, and NLP pipelines.
  • > Agentic Systems: Multi-agent coordination with Google ADK and tool-calling assistants.
  • > Backend Engineering: High-performance FastAPI, Flask, WebSockets, and PostgreSQL.
  • > Mobile & Web: Kotlin & Jetpack Compose, Flutter, Next.js, and offline-first apps.

~/experience/internships.log

experience[]

Alkhidmat Foundation Pakistan Information Technology Intern Jul 2026 – Sep 2026
  • Led development of QATRA, an emergency blood response platform, as part of a 6-person cross-functional team
  • Engineered full-stack backend with FastAPI + Supabase to match verified patients with nearby donors across Karachi in real time
  • Designed an Apple HIG-compliant Progressive Web App with real-time Leaflet geo-mapping and an interactive directory of 80+ Karachi hospitals
  • Built automated hospital-slip OCR processing pipeline and cryptographic CNIC identity verification to eliminate fraudulent emergency requests
  • Implemented in-memory TTL caching and SQL query optimization achieving sub-2s emergency feed response times
  • Automated CI/CD workflows on GitHub Actions with Pytest suites and zero-downtime deployments
FlyRank ML Engineering Intern Jun 2026 – Sep 2026
  • Delivered ML engineering capstone on content opportunity scoring — identifying high-impact content gaps from search performance data
  • Trained a Random Forest classifier with feature engineering across engagement, recency, and authority signals
  • Achieved Precision@50: 0.740 versus 0.340 baseline — a 2.17× lift in identifying top opportunities
  • Built a full Precision@K evaluation framework for comparing model variants and ranking strategy iterations
  • Documented findings as a research-grade report with reproducible Jupyter notebooks
DevelopersHub Software Development Intern Jul 2025 – Sep 2025
  • Built a Flask + SQLAlchemy task management system with Jinja2 templating, RESTful routing, and SQLite persistence; added full Unittest coverage
  • Upgraded to an Enhanced FastAPI version with Pydantic v2 validation, async endpoints, and comprehensive test suites
  • Implemented JWT-based authentication with token refresh flows and role-based access control
  • Integrated WebSocket real-time communication for live collaboration using FastAPI's native async WS support
  • Designed and maintained PostgreSQL schemas with migration scripts and query-optimized indexes for production workloads
CodeAlpha Python Development Intern Jul 2025 – Aug 2025
  • Built a collection of interactive Streamlit web applications with real-time external REST API integrations and live translation utilities
  • Developed an AI-powered chatbot with context-aware dialogue handling and Python NLP tooling
  • Implemented algorithmic automation scripts covering data scraping, file processing, and batch operations
  • Created a Python desktop app (Tkinter) with Fernet symmetric encryption, password hashing, and encrypted local note storage
  • Applied clean code principles, modular architecture, and documented all deliverables with README guides

spotlight://flyrank-ai

ML & Search Intelligence

FlyRank-AI: Machine Learning Engineering Capstone achieving Precision@50: 0.740 vs 0.340 baseline for content opportunity scoring using Random Forest and precision ranking.

language_distribution.json

languages[]

Python: 29 TypeScript: 7 Kotlin: 2 Java: 3 C++: 1 SQL: 1 Dart: 1 Shell: 1

all_projects --source github --count 12

showing: 12 / 12 repos

tech_stack --print

languages

Python TypeScript JavaScript Kotlin C++ Java SQL Dart HTML5 CSS3

ai_ml_data

Scikit-learn TensorFlow PyTorch Pandas NumPy Matplotlib Seaborn spaCy Sentence-Transformers ChromaDB Google ADK Random Forest Monte Carlo Simulations

frameworks_tools

FastAPI Flask Next.js 16 Streamlit Jetpack Compose Flutter SQLAlchemy Git Docker Supabase Firebase Tailwind CSS v4 Railway

databases

PostgreSQL MySQL SQLite ChromaDB Supabase Firebase Firestore Oracle

tools_concepts

Agentic AI RESTful APIs JWT Authentication WebSockets E2EE Encryption Pytest Unittest SDLC System Architecture Technical Documentation

$ collaborate --with abdulhayykhan

Interested in AI engineering, backend systems development, or intelligent product collaboration? Let's connect and build something valuable.

github --open linkedin --connect download cv