Vasanth Aggala

GT Movies Store is a full-stack web app that mimics an online movie renting and purchasing website, built around strict user stories.

• Followed an iterative Agile development approach, building and testing features incrementally.
• Used the required user stories to define the functionality and requirements for each feature.
• Broke larger features into smaller tasks and tested each component throughout development.
• Resolved questions and doubts through debugging, documentation, experimentation, and testing.
• Continuously tested features against the user stories and refined the application throughout development.

Developed an automated system using a Raspberry Pi to control a Pokémon emulator (mGBA), simulating gameplay and using pixel-based detection to identify rare encounters (Different colored Pokémon that have a 1/8192 chance of spawning). Integrated GPIO-controlled LED alerts and debugged input reliability and detection accuracy.

Reproducing CO adsorption site preference on Pt(111) and Cu(111) using DFT. Compared atop and FCC hollow binding energies on a high performance computing cluster. Found that the FCC hollow site is more stable for these two metals.

VibeRank is a real-time, gamified social media app where users vote on each other's “vibe” and compete on a live leaderboard. This project taught me a lot about integrating backend systems into Swift and also challenged my UI development skills.

This very website you are on right now! Prioritized clean UI and smooth animations to make seeing my work an easy experience.

Built a SwiftUI-based iOS app for journaling and mood tracking using MVVM architecture. Integrated Firebase Authentication and Firestore to support secure login and persistent, user-specific data storage.

Developed an end-to-end ML pipeline to predict movie revenue using structured features and text embeddings from plot summaries. Trained a Random Forest model and used RMSE/MAE and feature importance to evaluate performance and diagnose model behavior.

Built a data pipeline combining 95K+ flight records with weather and aircraft metadata by cleaning DOT datasets, normalizing schemas, and merging external sources. Also built a BeautifulSoup4 webscraper for parsing airplane tail numbers to join with airplane metadata.