Hi, I’m Aryan. I’m a CS student at UVA who likes building backend systems, solving real problems with code, and learning by building.
On my GitHub, you’ll find a mix of software engineering, machine learning, and full-stack projects. One of the projects I’m most proud of is a distributed Food Ordering System built with Spring Boot, Kafka, Docker, and the Outbox Pattern. It’s a microservices-based system focused on reliable communication and transactional consistency, and I built it from the ground up using Domain-Driven Design. I also built a UVA Course Picker, a JavaScript app that helps students optimize their schedules based on GPA, class timing, and professor preferences.
On the data side, I’ve worked on projects like Fake News Detection and Taiwan Bankruptcy Prediction using models such as XGBoost, SVM, and PCA. I’ve also experimented with event-driven systems in Python, CNNs for traffic sign recognition, and stock prediction models using KNN, logistic regression, and LSTMs. I’m always trying to learn more and really enjoy projects that sit at the intersection of software engineering and data-driven thinking. Thanks for checking out my work!
A backend microservices project built with Java, Spring Boot, Kafka, Docker, and PostgreSQL — simulating a full food delivery system with reliable event-driven messaging.
A JavaScript web app that helps UVA students optimize their course schedules based on GPA, professor ratings, and time preferences.
A real-time news aggregator and analytics platform powered by AI.
A real-time messaging app deployed with React (Vercel), FastAPI (Railway), MongoDB Atlas, and AWS S3 for file uploads. Built for low-latency communication with WebSockets.
A linear regression model trained on decades of NBA stats to forecast team wins based on point differentials and scoring metrics.
An NLP classification model that detects misinformation by analyzing news article content using TF-IDF and logistic regression.
A Convolutional Neural Network that classifies traffic signs with high accuracy, designed for use in autonomous vehicle systems.
A machine learning pipeline using XGBoost, SVM, and PCA to classify companies as bankrupt or not based on financial indicators.
Portfolio Website: https://aryanthodupunuri.vercel.app/
Feel free to connect or check out my work below 👇
Email: aryan20544@gmail.com