United States
IT Security and Trust II
Distracted Driver Detection : Worked on Facial landmark detection techniques that are built on deep neural network frameworks which will further lead to head pose estimation.
Course: ECE2514 Computational Engineering
Mobility and Connected Technology Department - Completed In-Vehicle Networking and Diagnostics Testing for S201, U321, W300 Projects and improved fault detection rate by 15%. - Developed Test scripts in CAPL for automated testing and updated the scripts as necessary to improve continuous integration practices. - Successfully deployed Wireless Charger in all upcoming models and designed test cases for system testing.
Completed the following projects during Training: - Integration of SRS system with HIL system using Piccolo Microcontroller - Development of program to automate testing on RPAS system. Worked on Object Identification on screenshot of Infotainment showing RPAS signal using OpenCV . - Simulation of the TPMS system in a vehicle and solving for optimal location of receiver and performing Real world measurements in vehicle to record the received signal strengths and compare it with the simulated values. - Two-week training on HiL system, both Software and Hardware Architecture