• Implemented artificial intelligence to app using CoreML (iOS) and TensorFlow (Android) with a custom models trained on datasets to perform efficient and accurate detection from live camera feed. • Implemented VIPER design pattern making app greatly decoupled and testable.• Used Dependency Injection to automatically handle dependencies for classes and objects.• Helped with the implementation of complex features i.e.: Fitting Room, Photo Activation• Trained and leaded offshore team of developers.• Reviewed pull requests and handled merge conflicts• Programmatically created custom UI and flows.• Implemented new features improving users shopping experience.• Debugged app using LLDB and Chisel• Used Charles to intercept calls and responses to fully test API integration.• Mocked API response using stubs.• Implemented comprehensive Unit test and Integration Test.• Translated technical user stories into working features.• Collaborated with cross-functional teams to define, design, and ship new features.

Socially Relevant Computing Research Experience for Undergraduates (REU) is funded by the NSF. I worked in the Video and Image Analysis Lab (VIA lab) where I modified a tool to work with my project and used deep learning to automatically learn features of actions to detect them in a video.