Shamitha Narra

• Automating network operations by developing a inhouse application using Angular, Flask, PostgreSQL, and Azure DevOps to replace NetBrain. • Implemented multithreaded APIs to retrieve and display real-time port information, significantly improving data retrieval efficiency for network devices. • Integrated Redis Cache technique to reduce the calls to DB with dynamic cache TTL. • Built dynamic front-end componets and modals to display device port details, enhancing user interaction and visibility of network data. • Optimized database schemas to ensure scalable and efficient management of network device information. • Leading the ongoing integration of Aruba network devices, automating port monitoring and control to improve network visibility. • Currently automating recurring network tasks via cron jobs, enhancing operational efficiency and reliability. • Refactoring the entire Backend Code based on the updated new DB schema and implemented CACHE for both UI and backend.

Teaching Assistant for COP 5536 - Advanced Data Structures

• Updating the lab's existing website using React. • Working on an AI/ML approach for sizing lung lesions and/or lung metastases to other organs.

• Real-Time Traffic Monitoring System Development: Spearheaded the development of a real-time traffic monitoring application, leveraging React for dynamic front-end interfaces and Node.js with Express.js for efficient backend services. Implemented PostgreSQL for robust data management, ensuring seamless processing of sensor data from thousands of urban traffic intersections. • Advanced System Architecture and Cloud Integration: Architected a secure, scalable infrastructure using Docker for containerization of both front-end and back-end components, and orchestrated deployment with Kubernetes on AWS EC2 for enhanced scalability and reliability. Automated data management tasks with AWS Lambda and secured user-specific access with Auth0 integration, while utilizing Amazon S3 for scalable cloud storage solutions.

• Enhanced the claims processing module at New York Life Insurance using microservices architecture with Spring Boot, decreasing response time by 30% and achieving scalability. • Streamlined CI/CD pipelines with Jenkins, Docker, BitBucket and reduced deployment times by 40%, leveraging AWS services for seamless infrastructure management. • Implemented Redis caching to store frequently accessed data, reducing database queries per request by 20% and enhancing system responsiveness for the claims processing module at New York Life Insurance. • Leveraged JPA for managing data persistence and complex queries in the claims processing module, improving database interaction efficiency and maintainability. • Utilized JIRA for project management, improved code quality with JUnit and Mockito, achieving 80% coverage. • Improved SLA compliance by enhancing system efficiency and responsiveness. • Integrated Grafana and Prometheus for real-time monitoring and metrics analysis, facilitating proactive system perfoRmance management and operational insights. • Designed and implemented Kafka messaging queues and topics, set up subscriber partitions, and managed offsets to ensure efficient and reliable message processing.

•worked on Java,sql •worked on temenos environment

•Researched and created a deep learning model for ASL(American Sign Language). •Worked on improving accuracy more than those of previous models. •Modeled facial expression recognition using Image Edge Detection and CNN, incorporating the Kirsch compass mask operator for scale normalization, gray level equalization, and edge detection in pre-processing. • Achieved an 86% accuracy by training the model with the Fer-2013 dataset combined with LFW.

Coursework Includes Data Structures, Object Oriented Programming, Design and Analysis of Algorithms, Operating Systems, Computer Networks, DBMS, Cloud computing. Hands on with - Unix, Java, Python, Image processing and Machine learning. Activities and Societies : Volunteer in NSS, ACM student chapter, technical clubs at IT department