Projects
Code with a purpose.
Building systems that solve real problems and scale with users.
I focus on delivering applications that are fast, scalable, and easy to maintain. Whether it's designing a dashboard, implementing OCR pipelines, or integrating APIs, I aim to build software that not only solves real problems but also contributes meaningfully to the world.
MavGrades.com
14,000+ Users
MavGrades is a platform that provides grade distributions for UTA courses and professors, helping students make informed class choices.
Next.js, TypeScript, Tailwind CSS, SQLite
FleetPulse
HackTX 2024 Winner
FleetPulse is a data visualization tool designed to help companies reduce carbon emissions for their truck and vehicle fleets.
Next.js, TypeScript, Tailwind, Cloudflare, Databricks, AWS, Clerk, PySpark, Scikit-learn, Random Forest, Multi-output Regression
Waste.0
HackUTA 6 Winner
Waste.0 is a web app designed to reduce food waste by using machine learning to predict optimal inventory levels and forecast item spoilage, minimizing surplus and waste.
Next.js, TypeScript, Tailwind, MongoDB, Databricks, AWS, Streamlit, Clerk
LegalAI
HackSMU VI Winner
LegalAI is an AI platform that simplifies legal document review by summarizing contracts, spotting risks, and offering key insights with advanced language models.
Next.js, TypeScript, Tailwind, MongoDB, PropelAuth, UploadThing, Open AI
Goblin
A robust expense management web app built with .NET, designed to streamline tracking, managing, and analyzing your financial transactions effortlessly.
C#, .NET, SQL, Azure, Docker
Service Request System
An Android application developed with Java that enables users to place service requests to selected service providers.
Java, Android Studio, Firebase
UTA Datathon 2024 Website
Official website of UTA Datathon 2024 for registrations and general information.
Next.js, TypeScript, Tailwind CSS, Firebase, Vercel
ACM UTA Website
Official website of Association for Computing Machinery (ACM) @ UTA.
Next.js, TypeScript, Tailwind CSS, Firebase Firestore
CBRE Asset Management
A machine learning model that predicts the maintenance needs in commercial building assets.
Python, Pandas, Scikit-learn, Random Forest, K-Means Clustering
Credit Card Fraud Detection
Exploratory data analysis and prediction model for credit card fraud detection.