I'm a third-year Computer Engineering student passionate about building real-world software systems that solve practical problems. My focus is on full-stack development, backend systems, and AI integrations, with strong emphasis on clean architecture, scalability, and production-ready code.

• 🏗️ Build end-to-end applications from frontend to backend to deployment
• 🔧 Design scalable backend systems with real-time communication
• 🤖 Integrate AI/ML capabilities into web applications
• 📦 Create open-source tools and NPM packages
• 🎯 Focus on system design, distributed systems, and best practices

• 📚 Sharpening fundamentals in DSA and Algorithms
• 🤖 Deep diving into Machine Learning and AI Model Integration
• 💡 Building AI-powered applications with focus on practical implementations
• 🧠 Exploring Deep Learning, NLP, and Computer Vision

📊 GitHub Statistics & Analytics

AI-powered study platform with PDF/YouTube link support, chat, summaries, transcripts, and quizzes

Tech Stack: React.js Express MongoDB FastAPI Gemini API Firebase Auth Tailwind CSS Cloudinary WebSocket Kafka TensorFlow

Key Features:

• 📄 PDF and YouTube content processing
• 💬 Real-time chat with WebSocket & Kafka
• 🤖 AI-generated summaries and quizzes
• 🎥 Video transcript generation

Enterprise-grade task and goal management system with AI planning and payment integration

Tech Stack: React.js Go (Golang) MongoDB PostgreSQL Gemini API Firebase Auth Razorpay Redis IndexedDB Brevo Webhooks

Key Features:

• 🧠 AI-powered task planning and suggestions
• 💳 Razorpay payment integration with webhooks
• ⚡ Real-time synchronization with Redis
• 📧 Email notifications via Brevo
• 💾 Offline support with IndexedDB

Generate ATS-compatible professional resumes from natural language prompts

Tech Stack: React Express MongoDB FastAPI Gemini API Firebase Auth Tailwind CSS Cloudinary

Key Features:

• 🤖 AI-powered resume generation
• 📋 ATS-compatible PDF export
• ☁️ Cloud storage with Cloudinary
• 🎨 Professional templates

Real-time 1-on-1 chat application with instant messaging

Tech Stack: React Express MongoDB Socket.io Firebase Auth Tailwind CSS

Key Features:

• ⚡ Real-time messaging with Socket.io
• 🔒 Secure authentication
• 💬 Private chat rooms

ArthaPage is a local-first AI browser extension that understands webpages, generates structured summaries, and enables interactive Q&A using both offline and online AI models. All chat history is stored in the user’s browser with no external database.

Highlights:

• 🔒 Local-first: chat history stored in the browser (no external DB)
• 🧠 Webpage understanding with structured summaries + interactive Q&A
• ⚡ Works with offline and online AI models

Enterprise-grade RPC cluster with load balancing, fault tolerance, and service discovery

Tech Stack: Node.js Express.js Load Balancer Fault Tolerance Service Discovery

Key Features:

• ⚖️ Automatic load balancing across server replicas
• 🛡️ Built-in fault tolerance and failover
• 🔍 Service discovery mechanism
• 📦 Easy setup and configuration

Lightweight, fast RPC engine for Node.js with client and server support

Tech Stack: Node.js Express.js Rate Limiting

Key Features:

• 🚀 Fast and lightweight
• 🔒 Built-in rate limiting
• 📡 Client-server architecture

Cross-platform CLI tool to inspect recent GitHub user activity

Tech Stack: Go (Golang) GitHub Events API

Key Features:

• 📊 View recent activity by user
• 🔍 Filter by event type and scope
• 💻 Cross-platform support
• ⚡ Fast and efficient

Quick local HTML file preview server for developers

Tech Stack: Express.js Node.js fs path

Key Features:

• ⚡ Instant local server setup
• 📁 Automatic file detection
• 🔄 Live reloading

Automatic file organization utility based on file types

Tech Stack: Node.js fs path

Intelligent file deduplication tool using hash-based detection

Tech Stack: Node.js CryptoJS fs path

Secure credential management system with encryption

Tech Stack: React Firebase Auth Firestore Tailwind CSS

Educational platform for student collaboration

Tech Stack: Django HTML CSS JavaScript

Modern blog application for tech enthusiasts

Tech Stack: Flask HTML CSS JavaScript

Stock price prediction and analysis tool

Tech Stack: Flask Data Analysis Machine Learning HTML CSS JavaScript

YouTube to MP3 conversion tool with API integration

Tech Stack: Flask JavaScript API Integration

3D platformer game built with Unity

Tech Stack: Unity C# Game Design

High-performance, modular backend for YouTube creators with AI/ML (PyTorch, Transformers) + time-series analytics + low-latency async processing

Tech Stack: Python TypeScript PyTorch Transformers TimescaleDB Async Processing

Key Features:

• 📈 Real-time trending insights & performance tracking
• 🧠 AI-assisted content strategy generation
• ⚡ Low-latency asynchronous pipeline design
• 🗃️ Time-series analytics using TimescaleDB

AI-powered attention monitoring system using facial landmarks, eye tracking, and head pose estimation

Tech Stack: Python OpenCV MediaPipe fastAPI ReactJS

Key Features:

• 👁️ Facial landmark detection for attention signals
• 😴 Eye tracking + head pose estimation
• ⏱️ Real-time monitoring pipeline
• 📊 Focus/attention evaluation logic

GPT built from scratch — assembled from NeetCode ML course submissions

Tech Stack: Python Maths

Key Features:

• 🧱 Transformer/GPT components implemented from fundamentals
• 🧠 Learning-focused implementations & experiments
• 🧪 Training/inference exercises from coursework

Minimal AI agent built from scratch using OpenRouter (Qwen), with planner-executor architecture + streaming

Tech Stack: JavaScript OpenRouter Gemini Async Iterators Streaming Generative AI

Key Features:

• 🗺️ Planner/Executor split via role-based prompting
• 🔁 Iterative execution loop
• 📡 Real-time token streaming responses
• 🧰 Minimal, from-scratch agent implementation

Controlled iterative tool-augmented agent where the LLM decides which function to call and loops until done

Tech Stack: JavaScript Gemini Generative AI

Key Features:

• 🧠 LLM-driven tool/function selection
• 🔁 Iterative reasoning + execution loop
• 🧩 Controlled architecture for reliable automation

AI agents like Copilot/Cursor take project context, call tools, and apply changes directly to files (context-aware coding automation)

Tech Stack: JavaScript Generaive AI Ai Agent Gemini

Key Features:

• 🧠 Context-to-LLM prompting flow
• 🛠️ Tool calling for real file operations
• ⚡ Real-time coding automation concept

🎨 Frontend Development

⚙️ Backend Development

🗄️ Databases

💬 Programming Languages

🤖 AI & Machine Learning

☁️ DevOps & Deployment

🔥 Currently Focused On Key Focus Areas: 🤖 Machine Learning Algorithms - Supervised, Unsupervised, Reinforcement Learning 🧠 Deep Learning - Neural Networks, CNNs, RNNs, Transformers 💬 Natural Language Processing - Text processing, Sentiment Analysis, LLMs 👁️ Computer Vision - Image Classification, Object Detection 📊 Data Science - Data Analysis, Visualization, Feature Engineering 🔬 ML Model Deployment - Integrating ML models in production apps

🎯 Future Learning Goals Planned Topics: ☁️ Cloud Platforms - AWS, Azure, Google Cloud 🐳 Containerization - Docker, Container Orchestration ☸️ Kubernetes - Pod Management, Scaling, Deployment 🔄 CI/CD Pipelines - GitHub Actions, Jenkins, GitLab CI 🏗️ Microservices - Service Mesh, API Gateway 📊 Monitoring & Logging - Prometheus, Grafana, ELK Stack

Following a strategic learning path focused on depth over breadth:

Status: Completed

• ✔️ Mastered advanced React patterns and state management
• ✔️ Explored Next.js and server-side rendering
• ✔️ Built production-quality full-stack applications

Status: Completed

• ✔️ Developed advanced REST APIs with FastAPI/Flask/Express/Go
• ✔️ Integrated AI models (Gemini API) into web applications
• ✔️ Built real-time systems with WebSocket and Kafka

Status: In Progress (Current Focus)

• 🚧 Learning ML algorithms and model training
• 🚧 Implementing Deep Learning with TensorFlow/PyTorch
• 🚧 Building NLP and Computer Vision projects
• 🚧 Deploying ML models in production environments
• 🚧 Exploring LLMs and advanced AI techniques

Status: Planned for Future

• 📖 Containerization with Docker
• 📖 Kubernetes orchestration
• 📖 AWS/Azure cloud services
• 📖 CI/CD pipeline implementation
• 📖 Microservices architecture
• 📖 Infrastructure as Code (IaC)

Status: Ongoing

• 📖 Building core components from scratch ("Build Your Own X")
• 📖 Implementing algorithms and data structures
• 📖 Exploring distributed systems
• 📖 System design and scalability patterns

"Deep understanding of fewer technologies > Shallow knowledge of many technologies"

I believe in:

• 🎯 Quality over Quantity - Master each technology thoroughly
• 🏗️ Building Real Projects - Learn by creating production-ready applications
• 🔄 Continuous Improvement - Regular refactoring and optimization
• 📚 Strong Fundamentals - Understanding core concepts before frameworks
• 🤝 Open Source Contribution - Sharing knowledge through code

const navnath = {
  code: ["JavaScript", "TypeScript", "Python", "Go", "Java", "C++"],
  focus: ["Machine Learning", "Deep Learning", "AI Integration"],
  currentlyLearning: ["TensorFlow", "PyTorch", "NLP", "Computer Vision"],
  futureGoals: ["Docker", "Kubernetes", "AWS", "DevOps"],
  askMeAbout: ["Web Dev", "Backend Systems", "AI/ML", "RPC Systems"],
  funFact: "I believe code is poetry in logic form"
};