Eshagh Kargar

- Worked on 3D object detection based on AVOD and PointPillars methods using TensorFlow and Pytorch. - 3D point cloud ground removing and clustering using PCL library in C++. - Implemented ROS nodes for ground removing, clustering, and 3D object detection in C++ and Python.

- Used deep learning to perform human activity recognition, achieved 94% accuracy, user heading estimation, obtaining 1.5 degrees mean error, and step length estimation. - Applied sensor fusion techniques such as Kalman and Particle filters for indoor positioning using Wi-Fi, Bluetooth, and IMU. - Used computer vision and deep learning to perform cattle detection and tracking, cattle's body segmentation, cattle's ID identification, lameness detection, and body condition score estimation.

 Programmed Siemens and HIMA DCSs and PLCs.  Commissioned and programmed DCS networks such as Ethernet and Profibus.

 Commissioned and programmed different systems such as Paging, CCTV, LAN, IDS, Clock.

 Designed boards and programmed them to simulate different conditions of the motor for Electronic Control Unit calibration.  Built and coded a package to test and confirm the performance of different relays in the car at the MEGA motor library.

The program covers topics including deep learning, computer vision, sensor fusion, localization, controllers, vehicle kinematics, automotive hardware, and more.

GPA: 18.78

GPA: 16.96