Pranav Balaji

Computer Science Student & AI Engineer

Passionate about machine learning, full-stack development, and creating innovative solutions. Currently pursuing my Bachelor's at Purdue University.

About Me

I'm a passionate Computer Science student at Purdue University with a strong focus on artificial intelligence and machine learning. My journey in tech has led me through various exciting projects and internships where I've applied cutting-edge technologies to solve real-world problems.

From developing sports betting models with machine learning to creating full-stack applications, I love turning complex ideas into elegant solutions. I'm particularly interested in the intersection of AI and practical applications.

Bachelor's in Computer Science, Purdue University
Expected Graduation: May 2027
West Lafayette, Indiana

Education

Purdue University

Bachelor of Science in Computer Science

Expected May 2027

Relevant Coursework:
Data Structures & AlgorithmsPython ProgrammingData ScienceC ProgrammingDiscrete MathematicsLinear AlgebraMATLAB Computing

Experience

AI Engineer Intern

Staples

Upcoming
Jun 2025 – Aug 2025
Boston, MA

Incoming Software Engineering Intern Summer 2025 (AI Intern)

Data Science Intern

Indian Institute of Technology Bombay

July 2024 – Aug 2024
Bombay, IN
  • •Developed a custom data processing workflow using R programming language and the dplyr library, enabling efficient analysis of large-scale wage data from the National Survey of the Government of India (over 20,000 individuals)
  • •Created and applied advanced statistical models using R to identify key factors influencing 5% wage distribution
  • •Designed and implemented a customized data visualization toolkit using ggplot, generating 4 comprehensive charts and graphs
  • •Wrote a detailed report summarizing the analysis, presenting key findings, and provided recommendations

Robotics Mentor / Lead Programmer

First Robotics #15089

October 2021 – Jan 2024
Boston, MA
  • •Designed and implemented advanced odometry programs using Java, enhancing autonomous robot functions by 80%
  • •Engineered and coded presentation to educate over 75 students from 7th to 10th grade on the four pillars of OOP

Projects

Sports Betting Models

Jan 2025 – Feb 2025

Engineered a Random Forest Regression model using scikit-learn on 8,000+ NBA player logs, predicting points, assists, and rebounds with 65% accuracy.

Key Highlights:

  • •Real-time data pipeline processing 1,200+ game odds per week
  • •Advanced feature engineering reducing MAE by 12%
  • •Live updates every 15 minutes with automated recommendations
PythonPandasNumPyOdds APIScikit-LearnPostgreSQL

AI/ML Movie Library

Nov 2024 – Dec 2024

Developed a full-stack web application that utilizes Django and React to deliver personalized movie recommendations through a custom machine learning model.

Key Highlights:

  • •Achieved Precision@20 score of 0.75 and Recall@20 of 0.6
  • •RESTful API with JWT authentication
  • •Database of 45,000 movies with efficient retrieval
PythonDockerGitReactDjangoScikit-LearnPostgreSQL

Portfolio Website

Sep 2024 – Nov 2024

Designed and developed a personal portfolio website utilizing Next.js and CSS, showcasing collections of projects.

Key Highlights:

  • •Responsive design with modern UI/UX
  • •Optimized performance and SEO
  • •Interactive project showcases
ReactNext.jsCSSJavaScript

Flappy Bird Game

Nov 2022 – Jan 2023

Developed a classic Flappy Bird clone using Java with custom graphics, physics engine, and scoring system.

Key Highlights:

  • •Implemented collision detection and gravity physics for realistic bird movement
  • •Created dynamic pipe generation with randomized heights and spacing
  • •Built high-score tracking system with persistent data storage
JavaSwingAWTObject-Oriented Programming

Quebec Election Data Analysis

Nov 2023 – Jan 2024

Scraped and merged 14 different datasets on election polls and demographics to conduct comprehensive Quebec election analysis.

Key Highlights:

  • •Analyzed factors like age, gender, ethnicity, region, income, and housing to predict voting patterns
  • •Used linear and logistic regression with KNN clustering achieving 82% accuracy across 27 political parties
  • •Focused on visual data presentation using tidyverse and ggplot2 for clearer insights
RKaggletidyverseggplot2Statistical Modeling

Skills

Languages

PythonJavaCC++JavaScriptHTML/CSSSQLMATLABRDartGroovy

Frameworks

ReactSpring BootFlutterAngularNode.jsDjangoFast-APIMaterial-UIJenkins

Developer Tools

GitDockerPostman APIAndroid StudioAWSGoogle CloudVS CodeEclipseJira

Libraries

PandasNumPyMatplotlibscikit-learndplyrtidyverseggplot2

Get In Touch

I'm always open to discussing new opportunities, interesting projects, or just having a chat about technology!

Contact Information

Location

West Lafayette, Indiana

Send a Message

© 2024 Pranav Balaji. Built with Next.js and Tailwind CSS.