About

Amir Pourshafiee is a highly skilled software engineer with a strong background in computer vision. He has a keen interest in SLAM, machine learning, deep neural networks, and calibration. With over 7 years of relevant experience, Amir has worked on various robotics and computer vision projects across multiple industries. Currently, Amir is working as a Senior Software Engineer at Magic Leap, where he collaborates with cross-functional teams to define system requirements for SLAM, calibration, 3D reconstruction, and marker detection. He is responsible for designing experiments, collecting and analyzing data, and identifying potential/future issues through early simulation/experimentation. Amir also develops software, test apps, tools, and metrics for profiling and benchmarking computer vision components. Prior to his current role, Amir worked as a Graduate Student Researcher at the University of California Santa Cruz, where he conducted research on robotics, computer vision, machine learning, SLAM, image processing, and sensor fusion. He designed a cancer cell growth monitoring software based on computer vision, performed localization using signal strength-based trilateration of RF modules on a network, and designed a high throughput, low latency Data Acquisition and Handling System for a NASA drone interfacing a Hyperspectral Density Camera, Thermal Camera, Laser Range finder, Structure from Motion camera, GPS and INS Guidance System. Amir has also worked as a Junior Robotics Specialist at Danser Lab, where he wrote an automation software to communicate with the LabVIEW driver of a micromanipulator for semi-automatic adjustments and implemented power supply boards and sensor subsystems for two collaborative rovers. Amir holds a Master's degree in Computer Engineering and a Bachelor's degree in Electrical Engineering and Network and Digital Technology from the University of California Santa Cruz. He also has an AA of liberal arts in Math, Physics, and Engineering from De Anza College. In addition, Amir has completed a Computer Vision Nanodegree from Udacity. Amir's technical skills include computer vision, software engineering, machine learning, neural networks, Python, research scientist, backend, and image processing. He is a highly motivated and detail-oriented individual with a passion for innovation and problem-solving.