class MuhammadFezan:
def __init__(self):
self.username = "H0NEYP0T-466"
self.name = "Muhammad Fezan"
self.location = "Lahore, Pakistan 🇵🇰"
self.role = "AI Systems Engineer & Full-Stack Developer"
self.university = "Lahore Garrison University"
self.degree = "BSCS — 6th Semester"
self.email = "fezan1029@gmail.com"
@property
def tech_stack(self):
return {
"ai_ml": ["Multi-Agent Systems", "RAG Pipelines", "LLM Fine-tuning (LoRA/QLoRA)",
"Computer Vision", "Deep Learning", "FAISS", "Agentic Workflows"],
"llm_providers": ["OpenAI", "Anthropic", "Mistral", "Groq", "Cerebras", "Grok",
"OpenRouter", "NVIDIA NIM", "Longcat", "GLM/Zhipu"],
"fullstack": ["React", "Node.js", "FastAPI", "MongoDB", "PostgreSQL", "WebSockets"],
"devops": ["Docker", "GitHub Actions", "AWS", "Vercel", "Railway", "Render"],
"languages": ["Python", "JavaScript", "TypeScript", "C/C++"],
}
def flagship_projects(self):
return {
"BTSC-UNet-ViT": "Brain tumor classification + segmentation — hybrid ViT + U-Net on 90k+ images",
"Dr.Document": "16-agent GitHub documentation generator — React + FastAPI + WebSocket streaming",
"DataForge": "LLM fine-tuning dataset platform — FAISS deduplication + multi-model routing",
"LinkedIn-Agent": "Autonomous LinkedIn presence manager — GitHub → LLM → Telegram → Selenium",
}
def current_mission(self):
return [
"🤖 Architecting production-grade multi-agent AI pipelines",
"🧬 Researching transformer-based medical image segmentation",
"📦 Building LLM fine-tuning infrastructure at scale",
"🌐 Shipping full-stack AI-powered developer tools",
]
|
Brain Tumor Classification + Segmentation Tech: PyTorch · ViT · U-Net · Medical Imaging research = {
"architecture": "Hybrid ViT + U-Net",
"dataset": "90,000+ medical images",
"tasks": ["Classification", "Segmentation"],
"approach": "Transformer-based deep learning"
} |
16-Agent GitHub Documentation Generator Tech: FastAPI · React · WebSockets · Multi-Agent · LLMs pipeline = {
"agents": 16,
"input": "GitHub Repository URL",
"output": "Full Documentation Suite",
"streaming": "Real-time via WebSockets",
"highlight": "Generated its own README 🤯"
} |
|
LLM Fine-tuning Dataset Platform Tech: Python · FAISS · Multi-Model Routing · LLMs platform = {
"deduplication": "FAISS vector similarity",
"routing": "Multi-model LLM ensemble",
"output": "Large-scale QA pair datasets",
"use_case": "Production LLM fine-tuning"
} |
AI-Powered LinkedIn Post Draft Assistant Tech: Terminal-Style · Python · Telegram · LLMs agent_loop = {
"source": "GitHub activity feed",
"generate": "LLM-powered post drafts",
"deliver": "Telegram approval bot",
"control": "You decide what gets posted"
} |
