CS Student & AI Developer
RABIA
ZULFIQAR
Building intelligent systems at the intersection of research and engineering — from lightweight computer vision models to full-stack AI platforms and large-scale data pipelines.
> console.log(
"Building the future"
)
Achievement
Philosophy
“Code with purpose, build with empathy, ship with confidence.”
Open to Opportunities
Internships & Full-Time
About Me
Who I Am
Hey there! I'm Rabia, a Computer Science student passionate about building intelligent systems. I engineer full-stack AI applications and RAG pipelines, work across data science and data engineering, and research lightweight AI architectures for on-device computer vision.
Education
FAST National University
Bachelor of Science in Computer Science
Technical Skills
Languages
Python
JavaScript
TypeScript
C++- SQL
Frameworks & Libraries
FastAPI
Flask
React
Next.js
Node.js- Laravel
Tailwind CSS- REST APIs
Data & AI
- RAG
- LangChain
- HuggingFace
- Gemini API
- CrewAI
- Google ADK
pandas
Plotly- Scipy
- pgVector
- ETL Pipelines
Databases
PostgreSQL
MySQL
MongoDB
Redis
Supabase
Tools & Infra
Docker
Git
GitHub
Linux- WebSockets
AWS
Azure
Experience
Data Science & Data Engineering Intern
2026Dun & Bradstreet (D&B)
Working across the Data Science & Data Engineering department — building and optimizing data pipelines, transforming large-scale datasets, and supporting analytics and modeling workflows.
AI Engineering Intern
Jun 2026The Botss
Optimized token usage for AI email agents to cut LLM consumption, built real-time voice AI with WebRTC, and shipped full-stack AI apps with chatbot session management, JWT auth, PostgreSQL, and an admin dashboard.
Research Assistant — Computer Vision
Feb 2026 – Apr 2026FAST National University
Implemented and evaluated a research paper on lightweight AI architectures for efficient on-device image processing, benchmarking performance and optimization trade-offs.
Projects
A 3D showcase of things I've built. Use the arrows, dots, or click a panel to bring any project into focus.
Initializing 3D space…
Writing
I'm starting to write about what I build and learn — AI engineering, data pipelines, and lessons from shipping real projects. First posts landing soon.
- AI EngineeringSoon
Building a RAG Pipeline That Actually Hits 85% Accuracy
A practical walkthrough of the retrieval stack behind SparkSpace — chunking, HuggingFace embeddings, and the evaluation loop that got accuracy production-ready.
8 min readDraft - Data EngineeringSoon
Lessons From the Data Engineering Trenches at D&B
What interning on large-scale data pipelines taught me about ETL design, data quality, and shipping analytics that teams actually trust.
6 min readDraft - LLM OpsSoon
Cutting LLM Token Costs Without Hurting Quality
Notes from optimizing AI email agents — prompt design, context trimming, and the trade-offs I measured between spend and response quality.
5 min readDraft
06 · Contact
Let's Build Something Together
I'm always open to new opportunities, research collaborations, and ambitious ideas. Drop me a line and let's talk.
