Ramsai Nelluri Email & Phone Number

Alpharetta, Ga, Us

United States

• Designed and implemented APIs using FastAPI to facilitate seamless interactions between Google Sheets and other cloud services, enabling efficient data operations like document creation, updates, and deletions.• Developed secure and robust connectors for various databases (e.g., SQL, NoSQL, Postgres Sql) and integrated them with cloud storage solutions, ensuring streamlined data transfer and real-time updates.• Utilized Google Cloud APIs, such as Google Sheets and Google Drive APIs, to automate document handling and user permissions, enhancing collaborative data workflows for end users.• Implemented both OAuth 2.0 and service account authentication methods to manage secure access to cloud resources, balancing user-specific access with application-level service accounts.• Built resilient error-handling mechanisms and integrated structured logging for API interactions, which improved system reliability and enabled faster troubleshooting of backend processes.

United States

I am working as a research assistant under Prof. Tarannum Shaila Zaman. As part of my research, I conducted extensive research focused on improving software debugging. The ultimate goal was to develop a systematic way to extract Unix commands from bug reports, and to use these commands to quickly fix software issues. Our research has the potential to revolutionize the software debugging process by identifying and simplifying the execution of UNIX commands to deal with reported issues. This can lead to faster bug fixes, improve software quality and enable users to use has increased satisfaction.

India

An improved ML model for audio event recognition, speech and speaker recognitionStep 1 - Speech and Speaker Introduction:In the first phase, our team developed a robust ML model for speech and speaker recognition. This model can automatically recognize voice commands, allowing for easy communication with smart home devices. Imagine saying "clean the house" or "turn off the TV," and your house responds immediately!Step 2 - Sound Event Description for Home Survey:Based on the success in Phase 1, we extended the application of our ML model in Phase 2. Now, it can identify and classify various noise events that are important for home monitoring needs. Whether it’s an alarm going off, a mirror opening, or a door opening, our model can detect and respond, increasing home security and peace of mind.

Vijayawada, Andhra Pradesh, India

Andhra Pradesh

I worked as a Teaching Assistant, collaborating on case studies related to the topics of Java, Machine Learning and Artificial Intelligence. I also encouraged friends and peers to collaborate on hands-on real-time projects.

Master'S Degree, Computer Science

Bachelor Of Technology - Btech, Computer Science