Manichandana Kandula Email & Phone Number

United States

Cincinnati, Ohio, United States

• Led a team of four in the development of the RAFvue project for UASI, enhancing reimbursement accuracy for healthcare facilities, which resulted in a 20% decrease in billing errors and a 15% revenue increase.•Engineered high-performance, HIPAA-compliant backend services, achieving a remarkable 40% increase in data processing and retrieval speed for sensitive 837p healthcare data.• Contributed significantly to the project by developing new features and consistently delivering ahead of schedule, utilizing Spring Boot for backend development, React.js for frontend, and MySQL for the database.

Cincinnati, Ohio, United States

Hyderabad, Telangana, India

• Engineered data pipelines using Apache Kafka, optimizing the migration of card information and reducing processing time by 25%, successfully managing the timely transfer of over 1 million card records.• Developed robust backend systems with Spring Boot, Spring MVC, and Spring Security, using Hibernate for efficient object-relational mapping (ORM), and Java 11 for application development.

• Managed the migration of Thomson Reuters' legacy application from on premises to AWS cloud infrastructure, achieving a 30% reduction in operational expenses and enhancing system scalability by 20%, resulting in a 50% increase in system efficiency.• Successfully transitioned the application database from Oracle to PostgreSQL, improving query performance by 35% and reducing database maintenance efforts by 40%, leading to a 25% boost in overall database efficiency.• Implemented Spring Boot's embedded Tomcat server to deploy standalone, production-ready applications with minimal configuration and setup.• Deployed and maintained applications on Amazon Web Services (AWS), utilizing Lambda for serverless computing, EC2 for scalable virtual servers, and API Gateway for efficient API management, ensuring reliable cloud-based solutions.

Kharagpur, West Bengal, India

• Implemented an IEEE paper “Boundary delineation of Agricultural fields in multi-temporal satellite imagery” on Machine learning using NumPy, Pandas, Rasterio.• The aim of the project is to derive closed polygons around the field from time series satellite imagery.• Implemented Raster Analysis to build boundaries within the fields.• Used Integrated method of edge detection and region-based detection together.• Implemented GIS Analysis using an open-source GRASS GIS tool to clean the raster result and convertinto final vector polygon.

Bachelor Of Technology - Btech, Computer Science

Master'S Degree, Information Technology