Hi, I'm Om Muley

This website is dedicated to the work of me, Om Muley - a student at Texas Tech University(TTU) studying Computer Science and Business. I will be graduating from Texas Tech with a BS in Computer Science in May 2026.

EXPERIENCE

SOFTWARE ENGINEER INTERN

May 2024 - August 2024

Texas Tech University

Developed a web application using SvelteKit to assist toddlers in learning proper word pronunciation.
Integrated Google Translation API for real-time pronunciation guidance.
Implemented progress tracking features using Firebase for real-time database management, storing user progress data such as word mastery levels, frequency of practice, and error patterns.
Utilized Chart.js to visualize progress data, providing users with insights into their learning journey and areas for improvement.
Applied machine learning with TensorFlow.js to tailor suggestions, enhancing individual learning outcomes by 18%.
Collaborated with psychologists and educators to ensure the app's features align with effective learning strategies.

FULL-STACK WEB DEVELOPER

April 2023 - June 2023

Texas Tech Writing Center

Designed and developed the website for Texas Tech’s writing center using Java and Angular to improve accessibility for people with special needs.
Improved accessibility, helping over 13% of students on campus more easily access the proper tools.
Led a team of 8 people, developing both the front-end and back-end of the web app to ensure a seamless user experience.

PROJECTS

Privacy Poll – Hack West Tx Winning Project

Developed PrivacyPoll, a Blockchain-based voting system using Zero-Knowledge Proofs for anonymity and fraud prevention, with built-in auditability for voters. Demonstrated strong database management skills, including table creation, SQL query execution, and error handling. Prioritized security with unique vote IDs and robust blockchain functionality. Led a team of four as Team Lead, overseeing front-end development with React.js and Web3.js for dynamic user interfaces integrated with blockchain features.

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Urban Forecast: Machine Learning for Real Estate Sales

Spearheaded a machine learning project focused on predicting residential real estate sales in Bristol using Support Vector Machine (SVM) models. Employed Python, Pandas, NumPy, and Scikit-learn for data analysis, model training, and evaluation. Successfully analyzed 20 years of Bristol real estate data (2001-2020), identified key trends, and trained an SVM model to deliver accurate market predictions for buyers and sellers. Developed a robust tool for forecasting real estate sales outcomes, contributing to informed decision-making. Utilized data visualization techniques to enhance data understanding and model performance evaluation.

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