
MS in Information Systems student and innovative aspiring Java developer with 3 years of experience in performance optimization and scalability solutions. Demonstrates proficiency in Java, React, Node and MySql with a proven track record of enhancing application performance and reducing system downtime. Committed to leveraging expertise in Scrum and collaborative skills to drive efficient project delivery and continuous improvement.
Programming Languages: Java, JavaScript, SQL, Python, PL/SQL
Database Management: MySQL, MongoDB
Testing/Security: JUnit
Web/Mobile Development: HTML, CSS, Angular
Development Tools: Maven, Git,
Software Engineering: System Analysis, Performance Optimization, Scalability Solutions
Frameworks/Platforms: Nodejs
Methodologies: Agile, Scrum, Test-Driven Development (TDD)
Cloud: Aws
Crop Disease Prediction using Deep Learning methods, Developed a cutting-edge crop disease detection and prediction model using YOLOv3 and ResNet-152, accurately detecting and predicting 38 diseases across 14 plant species in real-time. The user-friendly and scalable system improves accuracy by up to 95% compared to conventional methods, resulting in significant cost savings for farmers and ensuring food security. This powerful tool has the potential to revolutionize crop management and agriculture.
CommerceCraze, Developed CommerceCraze, an e-commerce web application, using Angular for a dynamic frontend and Node.js with Express for a scalable backend, incorporating MongoDB for effective data management. The platform features enhanced user experiences with dynamic product listings, a responsive interface, and secure transaction capabilities.