I build scalable backend systems and immersive frontends that blend performance, reliability, and design excellence. From secure Spring Boot microservices and REST APIs to React-based dashboards and intelligent ML-driven components powered by CI/CD pipelines - every line of code I write is aimed at seamless user experience and measurable impact.
Eastern Illinois University
Visvesvaraya Technological University
Redesigned and modernized the official Eastern Illinois University website with new web pages, improved accessibility, and mobile-first responsiveness using React, Tailwind, and Spring Boot.
Built a scalable, modular system improving UX, SEO, and content workflows across International Portal.
AI-powered receipt scanner and smart split engine that identifies items, extracts prices, and calculates individual shares automatically using OCR + Spring Boot + Salesforce integration.
Simplified expense sharing for users by automating receipt-based split calculations securely and accurately.
Built a full-stack digital banking platform with secure customer and admin modules, OTP-based transaction verification, JWT authentication, session management, and a clean React + Spring Boot architecture.
Provided a secure and seamless banking experience through verified digital transactions and reliable account management.
Java Full Stack analytics platform for operational data visualization and workflow automation. Achieved 75% reduction in manual effort and 60% improvement in data insights via Chart.js dashboards and optimized SQL workflows.
Empowered HR teams with instant data access and automated reporting, eliminating dependency on Excel sheets.
Contributed backend logic and PL/SQL automation for maturity date handling across financial departments. Focused on scheduling validation and data accuracy for banking processes.
Improved banking process accuracy and scalability through reliable scheduling and automation workflows.
AI-based Raspberry Pi robot for real-time waste classification and autonomous collection. Integrated with Blynk IoT for remote control, using Google Teachable Machine for ML model deployment.
Reduced manual labor in waste management through automated garbage identification and collection.
Built a Wi-Fi enabled garbage bin that sends alerts via Blynk when full. Used ultrasonic sensors and ESP8266 with Embedded C for cost-effective smart city waste solutions.
Enabled real-time waste monitoring by sending alerts when bins were full, improving city cleanliness efficiency.
Classified wine samples into quality levels using Logistic Regression, KNN, SVM, and Random Forest, with EDA and feature scaling.
Helped winemakers evaluate quality more accurately using data-driven classification techniques.
Built a regression model using Random Forest and XGBoost to forecast future gold prices based on economic indicators.
Enabled financial forecasting for investors by predicting commodity trends through machine learning.
Built a fraud detection model using Logistic Regression and SMOTE oversampling, achieving strong recall on imbalanced data.
Reduced undetected fraud cases by building a balanced model that flags anomalies in real time.