Enhancing tennis gameplay understanding using computer vision and deep learning by dissecting the components of a broadcasted tennis video including the court, players, and ball, and then converting those components to a digestible spatialized audio for blind and low-vision users. This project is conducted in the Columbia University Computer-Enabled Abilities Laboratory.
Developed a robust Command and Control (C2) software for a fleet of electrified UGVs. My contribution was divided into three main categories: autonomous features, embedded software features, and systems integration. Autonomy features included 3D-LiDAR-based collision avoidance and mission waypoint validation for autonomous navigation. Embedded software development included modular architecture design and implementation in C++. Lastly, system integration included sensor/actuator integration, testing, and characterization for functionality in harsh climate and terrain. 
Developed a complete hardware and software solution for car sharing including vehicle ECU and IOS app integration. Simply reserve an available car in your nearby proximity, walk up to the vehicle, and tap the ‘Unlock’ button on your phone. Drive to your destination, park the vehicle in any approved parking spot, and pay by the minute! 