Jagadeesh Undavalli

About Me

Hello! I'm Jagadeesh Undavalli, currently a Software Engineer at Persistent Systems. I hold a Bachelor of Technology in Computer Science and Engineering from Vishnu Institute of Technology, Bhimavaram, Andhra Pradesh. My expertise lies in Java, Python, SQL, MongoDB, and Machine Learning.

Throughout my academic and professional journey, I have worked on various projects that have honed my skills in software development and data science. I am passionate about leveraging technology to solve real-world problems and continuously strive to expand my knowledge and capabilities.

Career

Software Engineer

Persistent Systems Limited Oct 2024 - Present

Currently working on full-stack development, contributing to various projects and learning advanced concepts.

Software Engineer Intern

Persistent Systems Limited Jan 2024 - Sept 2024

Gained hands-on experience with key technologies, including JUnit, Maven, Spring, and Spring Boot.
Familiarized with Scrum and Kanban practices, enhancing my understanding of agile methodologies.
Participated in an internal hackathon, gaining insights into how a software engineer transforms an idea into a fully functional working model.

Education

Bachelor of Technology 2020-2024

Vishnu Institute of Technology, Bhimavaram, Andhra Pradesh CGPA: 9.25

Intermediate 2018-2020

Narayana Junior College, Vijayawada, Andhra Pradesh Percentage: 96.3%

High School (Class X) 2017-2018

Nirmala High School, Vijayawada, Andhra Pradesh GPA: 9.8

Projects

Prediction of Student Dropouts

Theme: Facilitate faculty in predicting student dropouts from their education.

Project Components:

Data Collection: Data gathered from government webpages and GitHub repositories.
Machine Learning Classifiers: Six diverse machine learning classifiers were developed and tested on the collected data.
Performance: RandomForestClassifier demonstrated superior accuracy and F1Score among the classifiers.
Deployment: Utilized Streamlit as the frontend to deploy the project on the cloud for enhanced usability and accessibility.

Source Code Deployment

Anonymous Vehicle Identification System

Theme: Utilizes machine learning to identify anonymous vehicles in parking areas.

Project Components:

Technology Stack: Employs optical character recognition (OCR) techniques for vehicle registration number extraction from images.
Database Integration: Compares extracted numbers against a pre-existing database using pattern recognition algorithms.
Fallback Mechanism: In cases of no database match, the system captures an image of the unrecognized vehicle.
Administrator Involvement: Sends captured images to administrators for manual verification and further action.
Efficiency: Seamlessly combines machine learning and image processing technologies to automate the monitoring and management of anonymous vehicles in parking spaces.

Source Code

DhaanAPI

Theme: Aims to create a versatile and user-friendly RESTful API using Flask to empower users with efficient database interaction capabilities.

Project Components:

Type: RESTful API
Technology: Developed using Flask library in Python
Description: DhaanAPI is a RESTful API developed using the Flask library in Python. It provides a platform for users to interact with a database, facilitating data retrieval, manipulation, and storage. This API offers a seamless and efficient way to access and manage data resources.

Source code Deployment link 1 Deployment Link 2