Full-Stack Development
Modern web apps, server architecture, and database design
Full-Stack Developer | Applied AI/ML Engineer
BS Computer Science undergraduate at UMT Lahore, dedicated to crafting resilient full-stack web applications with the MERN stack and developing high-precision AI/ML solutions driven by semantic search, recommendation engines, and dense vector retrieval.
const engineer = {
name: "Muhammad Faisal",
degree: "BS CS @ UMT Lahore",
stack: ["React", "Node", "MongoDB"],
ai_focus: ["BM25 + FAISS", "RL"],
status: "Available for Impact"
};
Background
I am a Computer Science undergraduate at the University of Management & Technology (UMT), Lahore (Class of 2022–2026), with a deep passion for building scalable, high-impact software systems. My technical focus converges on two complementary domains: modern full-stack development with the MERN stack and Applied AI/Machine Learning.
In full-stack engineering, I specialize in crafting clean architectures, building robust RESTful APIs, implementing granular Role-Based Access Control (RBAC), and optimizing database transactions. Simultaneously, my AI/ML work explores information retrieval, hybrid search engines (combining lexical and dense semantic embeddings), and adaptive recommendation systems with continuous feedback loops.
I take pride in writing clean, modular code, keeping performance at the forefront, and turning complex computational challenges into elegant, intuitive digital experiences.
Building secure, scalable, and responsive web platforms utilizing React, Node.js, Express, and MongoDB.
Engineering hybrid retrieval systems with BM25, FAISS, sentence embeddings, and RL feedback loops.
Rigorous study in data structures, algorithms, databases, and machine learning theory at UMT Lahore.
Expertise
Modern web apps, server architecture, and database design
Vector retrieval, ranking models, and NLP pipelines
Version control, API testing, and computational environments
Portfolio
Production-grade MERN e-commerce engine featuring user session persistence, JWT authentication, dynamic client-server shopping cart engine, Stripe sandbox payment checkout integration, and automated inventory deduction logic. Deployed on Render and Vercel.
Research-grade hybrid recommendation and discovery engine engineered in Python. Combines sparse lexical keyword retrieval (BM25) with dense semantic vector indexing (FAISS) powered by sentence-transformers, paired with an adaptive Reinforcement Learning (RL) feedback loop.
Real-time asynchronous task management platform built with MERN stack. Features live calculating analytics widgets (completion percentage, pending, completed counters), Kanban Board vs Tabular view toggles, client-side search filtering, and cloud database state sync.
Enterprise MERN CRM platform designed for customer lifecycle management (New, Contacted, In Progress, Closed). Features Role-Based Access Control (RBAC) separating Admin and Employee permissions, JWT authentication, and pagination.
Milestones
Responsible for meticulous data verification, auditing, and structural validation across large-scale datasets. Focused on maintaining uncompromising data integrity, identifying anomalies, improving validation pipelines, and adhering to strict quality benchmarks for operational efficiency.
Pursuing a comprehensive Bachelor of Science degree in Computer Science at UMT Lahore. Building deep theoretical foundations and practical expertise in software engineering paradigms, full-stack web technologies, machine learning, and advanced algorithms.
Let's Connect
Whether you're looking for a passionate Full-Stack Developer for your next project, an Applied AI/ML Engineer to build intelligent retrieval systems, or just want to chat about technology — my inbox is always open!