Bio

I'm an Graduate Student majoring in Computer Science at The University of Texas at Arlington.

After my undergrad, I have worked for as an Associate Member of Technical Staff at at Model N, where I've collaborated with the team in developing the "File API/ Document Store", a centralized file management system for Model N employees. It has been a great experience in learning new things and technologies.

I've completed my undergrad in Computer Science from Chaitanya Bharathi Institute of Technology, Hyderabad, India. I've also worked with various technologies ranging from Machine Learning to Web Development.

Projects

Food Delivery Application

ReactJS, Redux, Node.js, Express.js, MongoDB

Spearheaded the development of a comprehensive food delivery application with a team of 5, integrating essential features such as user authentication, Redux-powered cart management, and a payment gateway to enhance user experience and streamline the ordering process. Orchestrated the creation of user and admin dashboards, facilitating efficient management of users, products, and orders through intuitive interfaces and protected routes for administrative functions.

Booking Application

Full-Stack Development, ReactJS, Node.JS

Developed a full stack booking application with a team of 4, encompassing features such as user authentication, accommodation management, and booking functionality, including uploading photos and editing capabilities. Implemented a comprehensive suite of pages, including login/register, account management, detailed listings to build a robust web application using MongoDB, Express.JS, React.JS and Node.JS.

Shortest Path Distance Approximation using Deep Learning

Node2Vec, Word2Vec, Python

Developed a python application, with a team size of 2, which outputs an estimate of the shortest path between source and destination nodes using vector embeddings. Poisson regression gave the best result with a final accuracy of 87%.

You can see more projects on my Github Page.

Publications

DEEP REINFORCEMENT LEARNING FOR ROBOT PATH PLANNING WITH PERIODICALLY MOVING OBSTACLES: CURRENT METHODS AND CHALLENGES

Published in Neuro Quantology, November 2022

We address the problem of path planning for mobile robots in dynamic environments. We propose a learning-based approach that leverages spatial and temporal data to overcome the limitations of traditional planning algorithms in the presence of moving obstacles. The paper provides a comprehensive survey of deep reinforcement learning (DRL) techniques and their application in various navigation scenarios, including obstacle avoidance and multi-robot navigation. We also discuss the evolution of DRL-based navigation and highlight the challenges and potential solutions in this field.

Education

Master of Science - Computer Science (Aug 2023 - Present)

The University of Texas at Arlington

Cummulative GPA: 4 / 4

Bachelor of Engineering - Computer Science Engineering (Aug 2018 - July 2022)

Chaitanya Bharathi Institute of Technology, Hyderabad

Cummulative GPA: 8.36 / 10

Work Experience

I am interested in gaining more industry experience.

Associate Member of Technical Staff

Model N, Hyderabad (Aug 2022 - Jul 2023)

  • Proficient in Java and ReactJS, contributed to the development, testing, and enhancement of software features built for the manufacturers in the Life Sciences domain at Model N.
  • Wrote clean, well-tested code, and technical documentation for the Provider module, achieving 93% code coverage through unit testing using JUnit and Mockito.
  • Reduced task time from 60 to 5 minutes and improved efficiency by 80% in an Agile environment by writing a script that automates unit test execution.
  • Worked on the development of the “File API/ Document Store”, a centralized file management system for Model N employees. Utilized ReactJS, TypeScript, MariaDB, Apollo Client, and Prisma ORM to create an efficient platform for file storage, retrieval, editing, and seamless handling of large memory files.
  • Used Scrum and Agile processes to develop sophisticated, well-structured solutions.

Research IoT Intern

IIIT Hyderabad, Hyderabad, India (Apr 2021 - May 2021)

  • During the internship, I prioritized expanding my understanding of IoT technologies, with a particular focus on grasping the fundamentals, real-world applications, and hands-on implementation of IoT systems.
  • During the internship, I engineered and implemented a gas sensor system that detects leaks with 95% accuracy. It promptly notifies the owner via email and instant messaging, reducing the response time by 60%.

Web Development Intern

Brain o vision solutions, Hyderabad, India (Jun 2020 - Jul 2020)

  • Built a full-stack web application for placing orders for diagnostic tests through doctor prescription upload, which reduces the amount of paperwork, estimated at about 75%.
  • Collaborated with my project mentor to test and integrate new design capabilities. Adhered to best practices for web security. Troubleshot and debugged code ensuring compatibility with devices and browsers.