Team 26

Team Members

Faculty Advisor

Osvaldo Valerio
Alexey Pozdnyakov
Gordon Yang
Paul Hernandez
Justin Lin
Shaheer Siddique

Caiwen Ding


UConn Computer Science & Engineering Department

sponsored by
Sponsor Image Not Available


PartsFinder is a mobile application developed to make the finding of purchasable car parts easier. The app utilizes a machine learning model to predict uploaded images of car parts to make identification simpler for the user. We have designed a search that will remove redundancies and prioritize lower prices to make sure the user is getting the best deal possible. The frontend is built with React Native, a javascript framework designed for mobile application development. The backend is built with Python utilizing the Flask library and is being hosted on an Amazon Web Service (AWS) hosted service called Amazon Elastic Compute Cloud (EC2).