Building software that solves real-world problems.
Computer Science student focused on full-stack development, AI systems, RAG pipelines, and modern software engineering.
Overview
An architectural overview of my development philosophy, workflows, and technical stack.
Engineering Philosophy
I believe in building software that delivers immediate, tangible value. Rather than chasing theoretical abstractions, my focus is on product thinking, problem solving, and writing practical, maintainable code. I bridge the gap between engineering execution and product design, striving to solve real-world problems with solid architecture and artificial intelligence.
Current Focus
- Retrieval-Augmented Generation (RAG)
- AI applications & LLM Orchestration
- Full Stack Web Development
- Real-time Systems (WebSockets & Queues)
- Developer Experience (DX)
Open Source
Committed to learning in public and shipping high-quality, clean codebases. Active in developer ecosystems.
AI Pipeline
High-performance retrieval pipeline mapping dense vector indexing to Gemini model responses.
Realtime Architecture
Low-latency topology orchestrating Docker, Nginx, Redis caching, and Laravel queue workers.
UE Connect
ProductionA comprehensive university social network and academic mentoring platform integrating event-driven communication feeds with a self-hosted semantic advising AI pipeline.
Languages
GitHub Activity
Featured Projects
Production-grade systems and AI-powered infrastructure built to solve academic and real-time operations.
UE Connect
University Social Network & AI-Powered Academic Platform
A comprehensive university social network and academic mentoring platform integrating event-driven communication feeds with a self-hosted semantic advising AI pipeline.
University environments often lack integrated systems for students to communicate in real time, collaborate, and receive automated academic advising, leading to information fragmentation and advisor burnout.
UE Connect merges a high-fidelity community feed, direct websocket messaging, and advisor mentoring structures with a self-hosted semantic AI retrieval subsystem in a single platform.
Social Feed & Interaction
Event-driven posts, nested replies, media uploads, and custom user tag mentions (@mentions).
Real-time Communication
Low-latency direct messaging, visual presence trackers, and instant push notifications using Laravel Reverb and Redis brokers.
Academic Mentoring
Direct advisement queues matching student cohorts with designated faculty advisors for structured mentorship.
Integrates the HCMUE RAG Assistant, a self-hosted Retrieval-Augmented Generation pipeline. It parses institutional documents, indexes vector chunks into Qdrant using BGE-M3 embeddings, and uses Gemini to answer policy queries with strict citation references.
Successfully migrated institutional curriculum details into a semantic vector index, resolving student query delays and automating academic advisement workflows.
Supporting Systems
Independent modules powering specific operations within the platform.
A standalone backend service handling client WebSocket channels, message persistence, presence tracking, and server event broadcasting.
Configured a low-latency socket layer utilizing Laravel Reverb alongside Redis pub/sub to handle websocket event distribution and queue caching dynamically.
Provides reliable real-time messaging, instant push notifications, and presence trackers with sub-second message delivery overhead.
An interactive posting and communication package replicating standard high-fidelity social features like comments, nested replies, media uploads, and mentions.
Created custom regex-based text parsing filters that convert mentions to links, trigger asynchronous job workers for email/push notifications, and store uploads using standardized moderation checks.
Delivers Facebook-style posting features, clean nested replies, and immediate notifications when a user is tagged in posts or comments.
Engineering Capabilities
What I build, what problems I solve, and where I have hands-on experience.
AI & RAG Engineering
Built retrieval-based AI systems capable of searching, indexing, and reasoning over large academic datasets.
Highlights
- Processed 1,290+ academic PDFs into a structured knowledge base.
- Indexed over 11M tokens across 15K+ vector chunks in Qdrant.
- Built end-to-end RAG pipelines with semantic search and citation-grounded answers.
- Integrated Gemini for LLM orchestration and structured response generation.
Technologies
Technical Expertise
A structured breakdown of core paradigms and the technologies I utilize to build retrieval-augmented services and web architectures.
Core Expertise
Laravel Ecosystem
Designing service-layer MVC applications, database relations, task scheduling, and background queues.
AI & Retrieval
Engineering semantic retrieval systems, dynamic contextual chunking, vector database optimization, and LLM agent integration.
Realtime Systems
Orchestrating event broadcasting pipelines, state syncing, and high-frequency WebSocket messaging using Redis and Laravel Reverb.
AI & Retrieval
Vector database indexing and LLM pipelines driving semantic academic intelligence.
LLM orchestration and structured semantic generation.
Retrieval-Augmented Generation pipeline structures.
Vector database powering academic search workflows.
Dense mathematical context representations of text.
Cosine similarity scoring and proximity database search.
Multilingual embedding model mapping curriculum context.
Backend & Realtime
Service foundations and event-driven architectures powering systems logic.
Primary framework for large-scale web applications.
High-performance cache, pub/sub messaging, and queue broker.
WebSocket server broadcasting instant client events.
Structured relational database management and transactional storage.
Frontend & Languages
Reactive UI rendering and primary software engineering languages.
AI orchestration scripts, embedding generation, and data processing.
Typesafe frontend state management and reactive components.
Frameworks for building interactive user experiences.
Lightweight reactive frontend binding directly to backend states.
Let's Build Something Meaningful.
Open to software engineering, AI engineering, open-source, and product-building opportunities. Whether you want to collaborate on a system or just discuss retrieval-augmented generation pipelines, feel free to reach out.
- Backend Engineering
- AI & RAG Systems
- Full-Stack Development
- Open Source Collaboration