Hi, I'm Malik Mohammad Ammar

Full Stack AI Engineer

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.

Education

National University of Sciences and Technology (NUST)

2020 - 2024

Bachelor of Engineering — Electrical Engineering

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.

Computer Vision

NVIDIA Jetson

GStreamer

OpenCV

TensorRT

PyTorch

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.

Python

Scikit-Learn

NLP

TF-IDF

Tkinter

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

Projects

Check out my latest work

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.

Python

LangChain

Streamlit

LLM

RAG

ArXiv

DuckDuckGo

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.

Next.js

React

TypeScript

Tailwind CSS

Supabase

Vercel

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.

Python

OpenCV

PyTorch

YOLO

ROS

PID Control

TensorRT

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.

Python

OpenCV

PyTorch

YOLO

Raspberry Pi

Ultrasonic Sensors

Product Recommendation System

Built a hybrid recommendation system using NLP-based user profiling and content-based similarity with TF-IDF and cosine similarity.

Python

NLP

Scikit-Learn

Cosine Similarity

Tkinter

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.

Python

SVM

MLP

Random Forest

Scikit-Learn

PCA

Get in Touch

Want to chat? Shoot me a message and I'll respond whenever I can.

malikmammar17@gmail.com