# Malik Mohammad Ammar — Full Stack AI Engineer Portfolio

> Electrical Engineering student at NUST with hands-on experience in computer vision, AI/ML, and full-stack development.

## About

I am an Electrical Engineering student at NUST with a strong focus on computer vision, machine learning, and full-stack development. My experience spans deploying real-time object detection systems on NVIDIA Jetson platforms, building autonomous quadrotor simulations, and developing full-stack web applications.

I have worked as a Research Engineer at SINES, where I developed computer vision algorithms for autonomous systems, and as an intern at a Public Sector Research Lab, where I built ML-powered recommendation systems with 98%+ accuracy.

I am passionate about building intelligent systems that bridge the gap between AI research and practical, deployable applications — from edge AI on embedded devices to scalable web platforms.

## Skills

### Programming Languages
Python, C/C++, JavaScript, TypeScript, Verilog

### Machine Learning / AI
PyTorch, TensorFlow, Scikit-learn, NumPy, Pandas, OpenCV, Hugging Face, LangChain

### Web Development
React, Next.js, Node.js, Tailwind CSS, shadcn/ui

### Mobile Development
React Native, Expo

### Backend & Cloud Platforms
Supabase, Render, Streamlit

### Robotics & Simulation
ROS 2, PX4, AirSim

### Edge AI / Deployment
NVIDIA Jetson, TensorRT, DeepStream

### Developer Tools
Git, GitHub, Docker

## Experience

### Research Engineer — School of Interdisciplinary Engineering & Sciences (SINES) (May 2025 – Aug 2025)
Developed and deployed computer vision algorithms on the NVIDIA Jetson platform for object detection and ID-based object tracking with Re-ID, enabling autonomous behaviour. Built a low-latency video pipeline via GStreamer and OpenCV.

### Intern — Public Sector Research Lab (Jul 2023 – Sep 2023)
Built a hybrid skin-care recommendation system combining user-feature filtering and content-based similarity using TF-IDF and cosine similarity. Achieved 98.38% classification accuracy with Precision@10 = 1.00 and NDCG@10 = 1.00.

## Education

### National University of Sciences and Technology (NUST) — Bachelor of Engineering — Electrical Engineering (2020 - 2024)

## Projects

### OmniFinder AI
Agentic AI search engine with ReAct reasoning and multi-source RAG. Routes queries across Wikipedia, ArXiv & the web using intelligent classification — all through a Streamlit interface.
- GitHub: https://github.com/ammarmalik17/omnifinder-ai

### Salert
Pakistan's deal discovery platform aggregating sales, promotions, and discounts on clothing, food, and consumer items. Features geo-targeted deals, brand following, and voting system.
- GitHub: https://github.com/ammarmalik17/Salert

### Autonomous Quadrotor Object Tracking System
Deployed object detection and Re-ID tracking on NVIDIA Jetson using TensorRT, ONNX, and GStreamer/OpenCV. Validated autonomous quadrotor control via SITL and HITL simulations.
- GitHub: https://github.com/ammarmalik17

### Smart Cane for Visually Impaired
Developed on Raspberry Pi 5 using Python and OpenCV for real-time object detection. Integrated ultrasonic sensors for obstacle detection and audio alerts for safe navigation.
- GitHub: https://github.com/ammarmalik17

### Product Recommendation System
Built a hybrid recommendation system using NLP-based user profiling and content-based similarity with TF-IDF and cosine similarity.
- GitHub: https://github.com/ammarmalik17/skin-care-recommendation-system

### Heart Disease Severity Classification
Performed EDA using box plots, pair plots, and correlation matrices. Identified Triglycerides Level as key predictive feature via PCA, achieving 94.4% accuracy with an SVM model.
- GitHub: https://github.com/ammarmalik17

## Social

- GitHub: https://github.com/ammarmalik17
- LinkedIn: https://linkedin.com/in/malikmammar
- Email: malikmammar17@gmail.com