I’m a 2026 Computer Science graduate focused on building useful, responsive digital products across frontend and backend layers.
My work combines JavaScript, Node.js, REST APIs, PostgreSQL, Supabase and interactive web technologies. I care about clear interfaces, resilient systems and the small decisions that make a product feel finished.
EducationB.Tech — Computer Science & Engineering
FocusWeb Development / Full Stack / Interactive Web
LocationDubai, UAE
03SELECTED WORK
BUILT TO BE USED.
Selected projects from my full-stack and interactive web work.
PROJECT 01 FULL-STACK PLATFORM
The Void Space
A mobile-first wallpaper-sharing platform where creators manage profiles, upload work and publish through an approval workflow.
A responsive freelancer discovery and service-booking demo built for RabTech Academy, with 104 fictional talent profiles and a browser-local workspace.
A Django-based web application that detects malware in Android applications using machine learning algorithms. Trains and compares multiple classifiers (Naive Bayes, SVM, Logistic Regression, Decision Tree, Random Forest, SGD) with a VotingClassifier ensemble on Android app features.
Django web app with two user roles: Remote User (register, login, submit app details for malware prediction) and Service Provider / Admin (train models, view charts, download predicted datasets).
Extracts Android app features (App_Name, Category, Reviews, Size, Installs, Type, Price, Content_Rating, Genres, Last_Updated, Current_Ver, Android_Ver) from Android_Apps_Datasets.csv and classifies as "No Malware" or "Malware Detected".
Trains and compares 6 ML models with accuracy reporting, confusion matrices, and classification reports stored in MySQL.
Service Provider can view malware vs benign prediction ratios, user management, and download predicted results as Excel (.xls).
