Computer Science Spring Boot

Sai Adhinesh Reddy Tatireddy

Gainesville, Florida +1-352-***-**** **************@*****.*** linkedin/Sai Tatireddy Portfolio Education

University of Florida, Florida, United States August 2023 - December 2024 Master of Science, Computer Science CGPA 3.46/4

Manipal University, Jaipur, Rajasthan, India August 2019 - May 2023 Bachelor of Technology, Computer Science and Engineering CGPA 8.98/10 Skills

Languages: Java (17), JavaScript (ES6+), TypeScript, SQL, PL/SQL, Python, C++, Shell Script Web & Framework: HTML5, CSS3, Bootstrap, React.js, Redux, React Router, JSON, XML, Axios, Spring Boot, Spring MVC, Spring Security, Spring Data JPA, Hibernate, Resilience4j Backend & Databases: RESTful APIs, Microservices, Spring Web, Spring Core, Spring Cloud, Spring Cloud Gateway, Apache Kafka, Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, JDBC Cloud & Monitoring: AWS (EC2, Lambda, S3, RDS, IAM, CloudWatch), Docker, Kubernetes, Terraform, Jenkins, CI/CD, Maven, Gradle, Docker Compose, Prometheus, Grafana, ELK (Elasticsearch, Logstash, Kibana), SLF4J, Logback Testing & Tools: JUnit, Mockito, React Testing Library, Postman, Git, GitHub, GitLab, Jira, Confluence, Windows, Linux, macOS Experience

Full Stack Developer, UF Health September 2023 - Present

Led development of a medical web app using Spring Boot, ReactJS, and Oracle SQL, increasing ROI precision by 20% and optimizing analysis workflows for large datasets (~1TB) and image metadata storage.

Designed scalable REST-based microservices with Spring Framework, Spring Data JPA, Hibernate, and JDBC; enhanced performance using Spring Security, OAuth2, and JWT for secure API access.

Built PL/SQL procedures, triggers, and queries in Oracle DB to automate validation, aggregation, and secure storage of contoured data, ensuring data integrity and fast access.

Improved inter-service communication with Spring Boot REST clients (RestTemplate/WebClient) and centralized routing/authentication using Spring Cloud Gateway and Resilience4j circuit breaker.

Configured Apache Kafka clusters for real-time health record streaming; enhanced monitoring and debugging using SLF4J, Logback, Grafana, Prometheus, and log analysis with the ELK stack.

Developed CI/CD workflows with GitHub Actions, Docker, Kubernetes, and Maven; used AWS Lambda, S3, RDS, EC2, IAM for automation; ensured 90% test coverage with JUnit and Mockito. Frontend Developer, International Institute of Information Technology April 2021 - October 2021

Developed an admin portal for crop data using HTML5, JavaScript, CSS, ReactJS and TypeScript, revolutionizing human interaction and implementing multi-language support for broader accessibility.

Implemented RESTful APIs to connect the application to the backend services and REST API calls to reduce load times resulting in 15% increase in page speed.

Optimized React rendering performance by implementing custom hooks, reducing unnecessary re-renders by 40% and improving overall application responsiveness.

Leveraged Figma to craft intuitive UI/UX designs, significantly improving user experience by 30% and streamlining crop data visualization processes.

Projects

Home Finder

Designed and implemented human-centric features for the Home Finder platform using Django, Bootstrap, and JavaScript, enhancing the international student housing experience across web and mobile platforms.

Built a responsive, robust web application with HTML5, CSS3, JavaScript and Django; increased student engagement with over 1,200 monthly interactions by delivering intuitive UI/UX.

Leveraged PostgreSQL and Django ORM for data management; ensured cross-device compatibility with media queries and responsive frameworks like Bootstrap and Tailwind CSS.

Integrated search, filter, SMTP email notifications, and user authentication (with JWT) to boost functionality, client satisfac- tion, and user retention rates. Used Git and GitHub for version control and collaboration.

Employed Figma for rapid UI/UX prototyping, incorporating real-time user feedback to iteratively refine platform design aligned with user behavior and market expectations. Publications and Achievements

Windows Malware Detection using CNN and AlexNet learning Models, Springer 2022-LINK

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