Abdul Mueed Shahbaz

Architected a full-stack ecosystem using Spring Boot, Cloud, and Hexagonal Architecture with MySQL. Engineered an event-driven system and annotation-based auditing framework. Led frontend development using Vue.js and Quasar, creating a scalable library of 100+ components via Atomic Design. Integrated Microsoft Graph for complex approval workflows, implementing enterprise-grade RBAC and i18n localization.

Architected and led development of the OrderLab B2B platform: 22 Spring Boot microservices (MySQL, Kafka, Apache Ignite) supporting 100+ APIs with 99.9% uptime. Designed complex RFQ/Smart Ordering workflows, reducing manual processing time by 30%. Mentored team, enforced Clean Architecture, achieving >70% code coverage. Drove innovation via *WhatsApp API integration and exploration of Golang/Ethereum.

Architected and engineered a high-stakes e-assessment platform, automating 100% of the exam lifecycle with 99.9%+ reliability and anonymized AI-assisted grading. Designed a real-time AI proctoring system for sub-10s violation detection, enabling 1 proctor to manage 100+ examinees. Built the "rAdmin" self-service portal, reducing admin setup by 60%, and developed the examinee experience with a scientific editor and 100% MCQ auto-grading.

Built EzBridge, an influencer–brand collaboration platform with campaigns, chat, and Stripe escrow payments. Implemented secure authentication and integrated Facebook, Instagram, and YouTube APIs for portfolio imports and analytics. Developed reusable Vue.js components with the Decorator Pattern and improved reliability via structured logging and clean architecture.

Improved gameplay by designing a dynamic power-up system with five unique abilities and refining core mechanics like running, jumping, and animations. Resolved 20 environment issues and 10 UI bugs, enhancing level design and overall user experience.

During my internship supervised by New York University, I generated a training dataset of landscape features from high-resolution satellite imagery using Labelbox. This dataset was utilized for predicting the prevalence of vector-borne diseases and quantifying agricultural land.

Activities and societies: As a GDSC Core Team Member, I led and grew the ITU developer community by organizing technical workshops on Spring Boot, React, and cloud platforms. I also served as a Research Intern for the Intelligent Machine Labs (an ITU-NYU joint program), where I collaborated with faculty on advanced R&D, focusing on machine learning and data-driven systems.