Full Stack Developer with 2+ years of experience and 2+ internships specializing in MERN stack, Data Science, and Graph Databases. Worked at WESEE (Government/Defence) on naval data processing with Neo4j, PySpark, and Hadoop.
I am a Full Stack Developer and Data Science enthusiast with 2+ years of professional experience currently pursuing B.Tech in Computer Science at GGSIPU. With hands-on experience in the MERN stack and data analytics, I specialize in building scalable web applications and working with big data technologies.
Worked at WESEE (Government/Defence sector) as a Data Science Intern, where I worked with PySpark, Neo4j, Hadoop, and GraphDB for naval data processing and intelligence analysis. I have completed 2+ internships including Full Stack Developer at Mersate Fashion, building responsive UIs with Next.js and TypeScript.
My expertise spans from full-stack web development with React and Node.js to data science with knowledge graphs, anomaly detection, and model training. Passionate about solving real-world problems with technology and continuous learning.
B.Tech CSE at GGSIPU
Data Science Intern at WESEE
2+ Years & 2+ Internships
20+ Full Stack Projects
A comprehensive toolkit of modern technologies and frameworks I use to build exceptional digital experiences
WESEE
Government / PSU / Defence
Mersate Fashion
Manufacturing / Core
Tech Solutions Inc.
Technology / Software
A showcase of my best work - from AI-powered applications to full-stack web platforms
Full-stack, AI-driven waste management platform using Next.js, React, TypeScript, and Firebase. Integrated AI waste classifier achieving 95% accuracy, reducing sorting time by 70%. Real-time tracking with Leaflet.js, analytics dashboard, and gamified challenges boosting engagement by 85%. Serving 100+ users.
AI-powered Next.js application leveraging Google Gemini to generate engaging content for Twitter, Instagram, and LinkedIn. Features user authentication with Clerk, points-based system, content history and regeneration, responsive design, and preview functionality.
Advanced anomaly detection system for WESEE Defence using ML algorithms to process maritime data streams. Extracts key entities (vessels, locations, timestamps) from unstructured event data and identifies irregular patterns, suspicious activities, and potential threats. Real-time monitoring with automated alerts and intelligence dashboards.
Machine learning model for predicting customer churn in credit card companies. Uses Logistic Regression, Random Forest, and XGBoost. Achieved ROC-AUC score of 0.85 with strong predictive capabilities. Identifies high credit utilization, late payments, and low engagement as top churn indicators.
Comprehensive source tracking system with Neo4j GraphDB for defence intelligence. Extracts entities from event data (personnel, vessels, coordinates, incidents) and tracks data lineage across systems. Enables event correlation, provenance analysis, impact assessment, and compliance reporting with graph-based relationship mapping.
Interactive analytics dashboard for visualizing complex datasets and generating insights. Features real-time data processing, customizable charts and graphs, KPI tracking, and automated report generation. Built for data-driven decision making with drill-down capabilities and export functionality.
Full-stack food delivery platform built with MERN stack. Features seamless food ordering, secure user authentication, shopping cart functionality, Stripe payment integration, and admin panel for managing orders and users. Complete end-to-end food ordering experience.
Voice-activated chatbot using OpenAI library, capable of recognizing voice commands and executing tasks in real-time. Integrated speech-to-text and text-to-speech APIs for seamless interaction. Features predefined command responses for interactive user experience.
Government/Defence sector data processing system using PySpark, Neo4j, Hadoop, and GraphDB. Processes maritime datasets for intelligence analysis, anomaly detection, and knowledge graph construction. Real-time big data pipeline for naval operations.
Full-stack multi-vendor e-commerce platform built with MERN stack. Features vendor dashboards, product management, shopping cart, order tracking, payment integration with Stripe, real-time notifications, and admin analytics. Supports 1000+ products with advanced filtering and search.
Comprehensive property management platform with Next.js and TypeScript. Virtual tours with 360° images, mortgage calculator, property search with filters, booking system, landlord-tenant portal, rent payment tracking, and maintenance request management. Integrated with Google Maps API.
Full-featured LMS platform with course creation, video streaming, quizzes, assignments, progress tracking, and certification. Features live classes with WebRTC, discussion forums, grade book, payment integration, and student/instructor dashboards. Supports 500+ active learners.
HIPAA-compliant healthcare platform connecting patients with doctors. Online appointment scheduling, video consultations, prescription management, medical records storage, payment processing, appointment reminders via SMS/Email, and doctor availability management.
Full-stack social media application with user profiles, post creation, likes/comments, friend system, real-time chat, notifications, news feed algorithm, photo/video uploads, and privacy controls. Built with MERN stack and WebSocket for real-time features.
NLP-powered sentiment analysis system using transformer models (BERT). Analyzes customer reviews, social media posts, and feedback with 94% accuracy. Features multi-class classification, emotion detection, aspect-based sentiment analysis, and real-time processing API.
Real-time object detection system using YOLOv8 and TensorFlow. Detects and classifies 80+ object categories with bounding boxes. Supports video streaming, batch processing, custom model training, and RESTful API. Achieves 30+ FPS on edge devices.
Collaborative filtering recommendation system using matrix factorization and deep learning. Provides personalized product/content recommendations with hybrid approach (content-based + collaborative). Handles 100K+ users with A/B testing framework and cold-start problem solutions.
Milestones and accomplishments throughout my journey in tech
Worked as Data Science Intern on naval data processing with PySpark, Neo4j, and Hadoop
Built 20+ production applications using MERN stack, Next.js, and TypeScript
Specialized in Neo4j, GraphDB APIs, knowledge graphs, and source tracking systems
Experience with Hadoop ecosystem, PySpark, and large-scale maritime datasets
Developed responsive UIs with Next.js, TypeScript, and Tailwind CSS
Strong algorithmic skills with focus on data structures and optimization
Pursuing Computer Science Engineering with focus on Full Stack and Data Science
Experience in anomaly detection, model training, and intelligence analysis
Milestones and accomplishments throughout my journey in tech
Runner-up at Smart India Hackathon, demonstrating problem-solving and teamwork skills
Secured 2nd position in competitive hackathon with innovative solution
Peak rating of 1550+ with participation in 23+ contests, ranking in top 30% globally
Built and deployed multiple production-ready applications using MERN stack
Project BioBranch accepted for Google Summer of Code Extended program
Active technical member at Google Developer Student Clubs, GGSIPU
Completed Google Cloud Platform training and certification
Certified in Data Analytics from IBM Skills Build program