System Status

Current Mode

Collaboration

Base Location

class VibhorJoshi:
    def __init__(self):
        self.name = "Vibhor Joshi"
        self.role = "Machine Learning Engineer"
        self.education = "B.Tech (Pursuing)"
        self.location = "India 🇮🇳"
        self.languages = ["Python", "JavaScript", "TypeScript", "C++"]
        
    def get_expertise(self):
        return {
            "primary": ["Computer Vision", "GeoAI", "Deep Learning"],
            "secondary": ["Gesture Recognition", "Medical Imaging", "Web ML"],
            "tools": ["PyTorch", "TensorFlow", "OpenCV", "Flask", "React"]
        }
    
    def current_focus(self):
        return [
            "🧠 Advanced Medical Image Analysis",
            "🌍 GPU-Accelerated Geospatial AI",
            "🎮 Real-time Gesture Recognition Systems",
            "🔬 Healthcare AI Applications",
            "🌐 Scalable ML Deployment Solutions"
        ]
    
    def achievements(self):
        return {
            "model_accuracy": "90%+ (Medical Imaging)",
            "processing_speed": "~100ms (Duplicate Detection)",
            "automation_gain": "50% (File Management)",
            "deployment": "Multi-platform (Web + Desktop)"
        }

⚡ Core Arsenal

Python

JavaScript

TypeScript

C++

React

GitHub

🤖 AI/ML Powerhouse

PyTorch

TensorFlow

OpenCV

Scikit-learn

Keras

NumPy

Pandas

🌐 Full Stack Deployment

Flask

Django

Node.js

Next.js

Vercel

Docker

Git

🛠️ Development Toolkit

GPU-Accelerated GeoAI Framework for Large-Scale Spatial Analysis

🎯 Key Achievements:

• ⚡ GPU Optimization: 10x faster processing for large-scale imagery
• 🎯 High Accuracy: Robust handling of heterogeneous geospatial data
• 🏗️ Scalable Architecture: Template-based framework for building footprint extraction
• 🌐 Real-world Impact: Urban planning and infrastructure mapping

💡 Tech Stack: PyTorch • CUDA • GeoPandas • GDAL • QGIS

AI-Powered Medical Imaging for Tumor Classification

🎯 Key Features:

• 🏥 Clinical Grade: High-precision MRI analysis for tumor detection
• 🚀 Real-time Processing: Instant diagnosis with CNN architecture
• 📊 Visualization Dashboard: Interactive result interpretation
• 🌐 Cloud Deployed: Accessible via web interface on Vercel

💡 Tech Stack: TensorFlow • Keras • OpenCV • Flask • Vercel

Real-time Pose Estimation for Gesture-Based Gaming

🎯 Capabilities:

• 🎮 Low Latency: Real-time pose detection with <50ms response
• 🤚 Gesture Mapping: Custom control schemes for game integration
• 📹 Computer Vision: MediaPipe-powered pose estimation
• 🔧 Flexible Design: Adaptable to various gaming scenarios

💡 Tech Stack: Python • MediaPipe • OpenPose • OpenCV • PyAutoGUI

Intelligent Semantic Duplicate Detection System

🎯 Highlights:

• 🧠 AI-Powered: Semantic similarity using transformers.js (MiniLM/CLIP)
• ⚡ Fast Processing: ~100ms for text, ~200ms for images
• 🔒 Secure: SHA256 exact matching + semantic analysis
• 💻 Multi-Platform: Web (Next.js) + Desktop (Electron)

💡 Tech Stack: TypeScript • Next.js • Electron • transformers.js • FAISS

Multi-Disease AI Diagnostic Platform

🎯 Capabilities:

• 🏥 Multi-Condition Analysis: Predicts multiple diseases from symptoms
• 🤝 User-Friendly: Intuitive Streamlit interface
• 🔐 Privacy-First: HIPAA-compliant design principles
• 🔬 Ensemble Learning: Multiple ML models for robust predictions

💡 Tech Stack: Python • Streamlit • Scikit-learn • Pandas • NumPy

Agricultural AI for Plant Disease Detection

🎯 Features:

• 🌾 Crop Protection: Early disease detection for agricultural applications
• 📸 Image Classification: CNN-based leaf analysis
• 🛒 Marketplace: Integrated solution marketplace
• 🌍 Farmer Support: Accessible tools for agricultural communities

💡 Tech Stack: React • TensorFlow.js • Flask • Vercel

GitHub Statistics Dashboard

Language Distribution & Activity

Performance Indicators

Metric Category	Key Indicator	Value	Trend
🎯 Code Quality	Repository Health	A+	📈
⚡ Productivity	Commits/Week	25+	📈
🌟 Community Impact	Total Stars	Growing	📈
🔄 Collaboration	PRs & Issues	Active	📈
🧠 Innovation Index	Novel Solutions	High	📈
🚀 Deployment Rate	Production Apps	6+	📈

Achievement Showcase

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🎓 RESEARCH & LEARNING TRAJECTORY

🔬 Research Area	🎯 Focus	🛠️ Tech Stack	📈 Progress
Computer Vision & Medical Imaging	Tumor detection, Disease prediction, Image segmentation	TensorFlow, PyTorch, OpenCV, Scikit-learn
Geospatial AI (GeoAI)	Building footprint extraction, Urban mapping, Spatial analytics	PyTorch, GDAL, GeoPandas, CUDA
Gesture Recognition & HCI	Real-time pose estimation, Interactive controls, Gaming	MediaPipe, OpenPose, Python, OpenCV
Intelligent File Management	Semantic duplicate detection, Automated organization	TypeScript, transformers.js, FAISS, Electron
Web ML Deployment	Scalable model serving, API-driven applications	Flask, Django, React, Vercel, Streamlit
Data Engineering & Optimization	ETL pipelines, Data augmentation, Imbalanced datasets	Pandas, NumPy, Dask, Airflow, Apache Spark

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📝 CONTENT & KNOWLEDGE SHARING

Technical Writing

📝 Regular Contributor on Medium

Topics I write about:

• 🧠 Machine Learning Best Practices
• 🔬 Computer Vision Techniques
• 🌍 GeoAI Applications
• 🏥 Healthcare AI Solutions
• 💻 Full Stack ML Deployment

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🌐 CONNECT WITH ME

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💡 CURRENT FOCUS & COLLABORATION

current_work:
  - project: "Brain Tumor Detection System"
    status: "Production"
    url: "https://vercel.com/vibhor-joshis-projects/brain-tumor-classification-mri-scan"
  
learning:
  - Flask & Django for ML deployment
  - Advanced Deep Learning architectures
  - Cloud-native ML infrastructure
  - Scalable AI systems design

collaboration_open:
  - project: "Leaf Disease Predictor"
    type: "Open Source"
    seeking: "Contributors for agricultural AI"
    url: "https://leaf-disease-predictor-unub.vercel.app/market"

seeking_help:
  - project: "Multiple Disease Prediction System"
    areas: ["UI/UX improvements", "New disease models", "Data collection"]
    url: "https://publicmlwebapp-jiv44uyqzrjuznpfs6gnkx.streamlit.app/"

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🏅 EXPERTISE METRICS

Metric	Value	Status
Model Accuracy	90%+	🟢 Production
Processing Speed	~100ms	🟢 Optimized
Automation Efficiency	50% Gain	🟢 Deployed
Code Quality	A+ Grade	🟢 Maintained
Documentation	Comprehensive	🟢 Updated
Test Coverage	85%+	🟡 Improving

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🎯 DEVELOPMENT PHILOSOPHY

"Building AI solutions that bridge the gap between cutting-edge research and real-world impact. Every line of code is a step towards making intelligent systems accessible, reliable, and transformative."

Core Principles

🎯 Innovation First - Pushing boundaries with novel AI architectures
🔬 Research-Driven - Grounded in scientific rigor and experimentation
🌍 Impact-Focused - Solving real-world problems with practical solutions
🤝 Open Collaboration - Contributing to the ML community
📚 Continuous Learning - Staying ahead of the AI curve
⚡ Performance Obsessed - Optimizing for speed and efficiency

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🚀 FUTURE ROADMAP

graph LR
    A[Current State] --> B[Advanced Healthcare AI]
    A --> C[Scalable GeoAI Platform]
    A --> D[Production ML Systems]
    B --> E[Clinical Deployment]
    C --> F[Urban Planning Tools]
    D --> G[Enterprise Solutions]
    E --> H[Real-world Impact]
    F --> H
    G --> H

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2025 Goals

• 🎯 Deploy 5+ production-grade ML systems
• 🌍 Scale GeoAI framework to continental level
• 🏥 Clinical validation of medical AI models
• 📚 Publish research papers on novel architectures
• 🤝 Build open-source ML community
• 💼 Contribute to healthcare AI standards

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"Transforming Data into Intelligence, One Model at a Time"

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⭐ If you find my work interesting, consider starring my repositories!