Rishi

{

Rishi Naidu Chodavarapu

Age: 19,

School: University of Texas at Dallas,

Degree(In progress): Bachelor's in Computer science

}

About Me

I am a college student studying at University of Texas at Dallas. I have experience in programming languages like python, C++, java etc. As a student in Computer Science, I am eager to apply my technical skills and knowledge in a professional environment. I have a strong passion programming. During my academic studies, I have learned and gained experience and have completed several projects involving software development, database management, and web development.

Portfolio

As a computer science student, I am looking for an internship to work with experienced professionals and further develop my skills in a fast-paced, dynamic environment. I am excited to learn from my colleagues, take on challenging projects, and make a positive impact on the company's goals and objectives. As a kid I have always been the go-to-guy for any technical issues. I used to fix any technical issues in a phone or a laptop. I want to expand from what I was and go into software developing, which is a bigger department, and improve my skills.

I believe with my current technical skills, combined with my passion to learn and my strong work ethic, make me an ideal candidate for an entry-level software developer position. I look forward to the opportunity to work with a dynamic team and contribute to the success of the company.

My resume

My Work

Music Genre Classification Application

Distributed Systems Key-Value Store

Portfolio

Developed a music genre classification app using Python, TensorFlow, and Librosa.
Built a CNN model for data preprocessing and feature extraction.
Created a React interface for audio uploads and classification results.
Utilized GitHub for version control and teamwork, ensuring seamless collaboration and efficient project management.
Deployed the application on AWS, utilizing EC2 and S3 for scalable infrastructure.

Designed and implemented a scalable key-value store using a distributed systems approach.
Utilized gRPC and Protobuf for efficient inter-service communication.
Implemented consistency protocols such as leader election and replication to ensure data integrity.
Deployed the system using Docker, enabling containerized microservices.

Developed a web application that analyzes sentiment from social media posts using natural language processing (NLP).
Built and trained a deep learning model using TensorFlow to classify text sentiment as positive, negative, or neutral.
Integrated the model with a Flask API, with a React frontend for user interaction and result visualization.
Deployed the application on AWS, utilizing EC2 and S3 for scalable infrastructure.