Pennywise
An expense tracker that lets users log spending simply by typing it out like a text message.
Behind the scenes, it uses text categorization and Named Entity Recognition (NER) to identify the amount, the item, and automatically assign it to the correct category.
The app then compiles this information into clear summaries and insights, helping users spot patterns in their spending and make better budgeting decisions without the usual manual effort.
SubTrack
This app makes it easier to keep track of recurring subscriptions. Users can choose from common services or add their own, set reminders, and fully customize billing cycles down to any duration they want.
The focus was on keeping the interface clean and simple, so everything from viewing payment schedules to managing multiple subscriptions feels straightforward and easy to use.
PWagon
A deep learning system for real-time license plate detection, built using a convolutional neural network trained on a custom annotated dataset and paired with Google’s OCR for accurate text extraction.
The system has been adapted for Amber Alert networks and deployed on a Raspberry Pi 4, capturing images during emergencies and instantly sending alerts.
This simple frontend interface lets law enforcement enter suspected license plates, which triggers Amber Alerts around the last known location of the vehicle, enabling real-time monitoring and detection as the system scans for matches.
Cinemate
A web application designed to streamline movie selection for friend groups. Users can create groups, add friends, and vote together on movies, while the system generates recommendations based on the group’s combined genre preferences, cutting decision-making time.
This platform also includes a “Where to Watch” feature, showing up-to-date streaming availability with direct links to each movie, making it easy for the group to start watching without hunting for platforms.
