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GauravPatil2515/README.md
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Typing SVG


#!/usr/bin/env python3

"""
BOOT SEQUENCE: GAURAV PATIL
Initializing AI subsystems... 100%
"""

class TheHealthcareArchitect:
    """
    Where clinical intelligence meets deep learning infrastructure
    """
    def __init__(self):
        self.identity = {
            'name': 'Gaurav Patil',
            'education': 'B.E. AI/ML @ SIES GST (CGPA: 8.57)',
            'role': 'AI/ML Engineer | Healthcare AI Specialist',
            'mission': 'Deploy AI that saves lives at scale',
            'email': 'gauravpatil2516@gmail.com'
        }
        self.experience = [
            {'role': 'Frontend AI Intern', 'company': 'CoralOS', 'period': 'Dec 2025 - Present'},
            {'role': 'AI Research Intern', 'company': 'Pioneer Machines', 'period': 'Jun-Nov 2025'},
        ]
        self.production_systems = {
            'neuro_rag':   {'latency_ms': 29, 'chunks': 1438, 'dataset': 'ICD-10'},
            'retinal_seg': {'dice': '83.7%', 'accuracy': '96%', 'arch': 'U-Net++'},
            'derm_ai':     {'accuracy': '99.1%', 'kappa': 0.975, 'arch': 'ViT+GradCAM'},
        }

    def mission_statement(self):
        return "Hospital -> Brain -> Rocket -> Pill"

architect = TheHealthcareArchitect()
print(f"RAG latency: {architect.production_systems['neuro_rag']['latency_ms']}ms | DermAI: {architect.production_systems['derm_ai']['accuracy']}")

THE AI LABORATORY

🧠 Neuro-RAG

CLINICAL MENTAL HEALTH DIAGNOSTICS ┌────────────────────────┐ │ ICD-10 (14K+ lines) │ │ ↓ │ │ Semantic Chunking │ │ (1,438 chunks) │ │ ↓ │ │ FAISS Vector Index │ │ ↓ │ │ Flask Clinical UI │ │ 29ms Query Latency │ └────────────────────────┘

text

Stats:

  • 14,000+ lines processed
  • 1,438 semantic chunks
  • 29ms end-to-end latency
  • Zero hallucination via citations

👁️ Retinal Vessel Seg

DIABETIC RETINOPATHY DETECTION

graph TD
    A[Fundus Image] -->|Preprocessing| B[U-Net++ Encoder]
    B -->|Nested Skip| C[Feature Extraction]
    C -->|DRIVE Dataset| D[83.7 Dice Score]
    D -->|FastAPI| E[Real-time Inference]
    style A fill:#ff6b6b,stroke:#fff
    style E fill:#4ecdc4,stroke:#fff
Loading

Results:

  • 83.7% Dice Score
  • 96% pixel-wise accuracy
  • Beats vanilla U-Net baseline
  • Sub-1s inference latency

🩺 DermAI

EXPLAINABLE SKIN DISEASE CLASSIFIER

results = {
  'model': 'ViT',
  'dataset': 'HAM10000 (7-class)',
  'accuracy': '99.1%',
  'cohens_kappa': 0.975,
  'explainability': 'Grad-CAM',
  'llm': 'Llama 3.3 QnA',
  'deploy': 'Flask + SQLite'
}

Capabilities:

  • 99.1% classification accuracy
  • Grad-CAM heatmap overlays
  • LLM-powered patient Q&A
  • Treatment recommendation engine

⚔️ BATTLE RECORD ⚔️

╔══════════════════════════════════════════════════════════╗
║              HACKATHON DOMINATION                        ║
╠══════════════════════════════════════════════════════════╣
║  🥇 Bounty Hunters GenAI Sprint  RANKED #1 SOLO (2026)  ║
║  🏆 Code 4 Compassion            WINNER – AI Track      ║
║  🥈 BNB Chain Bombay Hackathon   2nd PLACE (Web3 + AI)  ║
║  🥉 OxygenIgnite @ NIT Goa       3rd PLACE              ║
║  🌱 ByteCamp Hackathon           TOP 3 Sustainability   ║
║  🎯 Deep Blue Season 11 Mastek   FINALIST               ║
╚══════════════════════════════════════════════════════════╝

🛠️ WEAPON SYSTEMS

Core Languages Deep Learning Arsenal RAG & LLM Stack
Python PyTorch LangChain
SQL TensorFlow HuggingFace
C Scikit-Learn Groq
JavaScript Docker FAISS

🧪 Specialized Stack: U-Net++ • Vision Transformers (ViT) • Grad-CAM • FAISS • Vertex AI • Detectron2 • MiDaS • Mask R-CNN • XGBoost • Sentence-BERT • MLflow • Streamlit


📡 REAL-TIME STATS

GitHub Stats GitHub Streak

Contribution Graph


🌊 CURRENT EXPERIMENTS

const currentMission = {
  projects: [
    {
      name: "DermAI – Explainable Skin Classifier",
      stack: "ViT + Grad-CAM + Llama 3.3",
      status: "COMPLETE — 99.1% accuracy",
      next: "IEEE paper submission"
    },
    {
      name: "Retinal Vessel Segmentation v2",
      stack: "U-Net++ + CORAL Loss + FastAPI",
      status: "IN PROGRESS — pushing past 83.7% Dice",
      next: "DRIVE + CHASE_DB1 multi-dataset eval"
    },
    {
      name: "Aelura – Decision-First AI Interface",
      stack: "React + Gemini API + Memory Graph",
      status: "UAT PHASE at CoralOS",
      next: "Production launch"
    }
  ],
  target: "Research models -> IEEE paper -> Production"
};

🎓 Experience & Leadership

🤖 Frontend AI Intern | CoralOS (Remote)

Dec 2025 – Present

  • 🧠 Building Aelura — decision-first AI interface with structured query routing (Fact / Navigation / Decision) via Gemini API
  • 🗺️ Built interactive Memory Knowledge Graph to visualize conversation history
  • 📊 Real-time market data dashboard for beta testing and UX validation
  • 🚀 Preparing system for User Acceptance Testing (UAT)

🏥 AI Research Intern | Pioneer Machines & Automation

Jun 2025 – Nov 2025

  • 📄 Built medical document analysis pipeline using Vertex AI
  • 📊 Indexed 10K+ PubMed articles with automated semantic chunking
  • ⚡ Achieved 29ms query latency on FAISS retrieval
  • 🔄 Improved clinical data throughput by 40%

⚡ IEEE – Technical Head

SIES GST | 2024 – Present

  • 🎓 Organized Technopedia for 2 years (500+ attendees)
  • 🤖 Delivered 6-hour ISL Recognition workshop for 50+ students
  • 🚀 Led AI/ML sessions at Technopedia 2024 (100+ participants)
  • ⭐ Technical Star Award — Dr. K Lakshmi Sudha

🌐 GDG – ML & DS Coordinator

2024 – 2025

  • 👨‍🏫 Mentored 100+ students on ML model design and deployment
  • 💻 Weekly office hours & peer-led hack sessions
  • 📚 Curriculum: model design → training → production deployment

🤝 INITIATE CONTACT


╔═══════════════════════════════════════════════════════════════════╗
║  "Medicine has the questions. AI has the pattern recognition.     ║
║   I'm here to write the code that connects them."                 ║
║                                           — Gaurav Patil          ║
╚═══════════════════════════════════════════════════════════════════╝



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